ISCA - International Speech
Communication Association


ISCApad Archive  »  2017  »  ISCApad #231  »  Resources

ISCApad #231

Sunday, September 10, 2017 by Chris Wellekens

5 Resources
5-1 Books
5-1-1Li Deng and Dong Yu, Deep Learning: Methods and Applications, Foundations and Trends in Signal Processing
Foundations and Trends in Signal Processing (www.nowpublishers.com/sig) has published the following issue:   

Volume 7, Issue 3-4                                                                                                                                                                   
Deep Learning: Methods and Applications                                                               
By Li Deng and Dong Yu (Microsoft Research, USA)       
http://dx.doi.org/10.1561/2000000039                                       
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5-1-2O.Niebuhr, R.Skarnitzl, 'Tackling the Complexity in Speech', Prague University Press

Tackling the Complexity in Speech

Author Oliver Niebuhr, Radek Skarnitzl (eds)
Publisher Univerzita Karlova v Praze, Filozofická fakulta
Release year 2015
ISBN 978-80-7308-558-2
Series Opera Facultatis philosophicae
Pages 230

The present volume is meant to give the reader an impression of the range of questions and topics that are currently subject of international research in the discovery of complexity, the organization of complexity, and the modelling of complexity. These are the main sections of our volume. Each section includes four carefully selected chapters. They deal with facets of speech production, speech acoustics, and/or speech perception or recognition, place them in an integrated phonetic-phonological perspective, and relate them in more or less explicit ways to aspects of speech technology. Therefore, we hope that this volume can help speech scientists with traditional training in phonetics and phonology to keep up with the latest developments in speech technology. In the opposite direction, speech researchers starting from a technological perspective will hopefully get inspired by reading about the questions, phenomena, and communicative functions that are currently addressed in phonetics and phonology. Either way, the future of speech research lies in international, interdisciplinary collaborations, and our volume is meant to reflect and facilitate such collaborations.

https://e-shop.ff.cuni.cz/books/monographs_eng/opera_facultatis_philosophicae_eng/tackling_the_complexity_in_spee_-1153

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5-1-3J.Li, L.Deng, R.Haeb-Umbach and Y.Gong, 'Robust Automatic Speech Recognition', Academic Press

 'Robust Automatic Speech Recognition'

  • The  first book that provides a comprehensive review on noise and reverberation robust speech recognition methods in the era of deep neural networks
  • Connects robust speech recognition techniques to machine learning paradigms with rigorous mathematical treatment
  • Provides elegant and structural ways to categorize and analyze noise-robust speech recognition techniques
  • Written by leading researchers who have been actively working on the subject matter in both industrial and academic organizations for many years

https://na01.safelinks.protection.outlook.com/?url=http%3a%2f%2fstore.elsevier.com%2fRobust-Automatic-Speech-Recognition%2fJinyu-Li%2fisbn-9780128023983%2f.&data=01%7c01%7cygong%40exchange.microsoft.com%7c3bd27ec380c8427e97e208d2975aca2a%7c72f988bf86f141af91ab2d7cd011db47%7c1&sdata=PRRo3i4DYNV1rNmVlhPMaHa0pUN4oi%2b1khyjctDXxjU%3d

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5-1-4Barbosa, P. A. and Madureira, S. Manual de Fonética Acústica Experimental. Aplicações a dados do português. 591 p. São Paulo: Cortez, 2015. [In Portuguese]

Barbosa, P. A. and Madureira, S. Manual de Fonética Acústica Experimental. Aplicações a dados do português. 591 p. São Paulo: Cortez, 2015. [In Portuguese]     


http://www.cortezeditora.com.br/manual-de-fonetica-acustica-experimental-1599.aspx/p

This manual of Experimental Acoustic Phonetics is conceived for Undergraduate and Graduate classes on areas such as Acoustic Phonetics, Phonology, Communications Engineering, Music, Acoustic Physics, Speech Theraphy, among others.  Starting with a theoretical and methodological presentation of Acoustic Phonetics Theory and Techniques in five chapters,  including a chapter on experimental methods, the book follows with detailed acoustic analysis of all classes of sounds using audio files from both European and Brazilian Portuguese as data.
All analyses are explained step by step using Praat. The audiofiles are available on the book web site and can be downloaded.  All techniques can be applied to any language, of course. Proposed exercices at the end of each chapter allow the teacher o evaluate the student progress.

 

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5-1-5Damien Nouvel, Inalco, Maud Ehrmann, EPFL,Sophie Rosset, CNRS. Les entités nommées pour le traitement automatique des langues

Les entités nommées pour le traitement automatique des langues

Damien Nouvel, Inalco, Maud Ehrmann, EPFL
Sophie Rosset, CNRS  

Le livre est disponible en ebook au prix de 9,90 euros.
(prix réservé aux particuliers - PDF lisible sur tout support - uniquement disponible sur iste-editions.fr)
Le livre est disponible en version papier au prix de 40,00 euros.

Le monde numérisé et connecté produit de grandes quantités de données. Analyser automatiquement le langage naturel est un enjeu majeur pour les applications de recherches sur le Web, de suivi d'actualités, de fouille, de veille, d'opinion, etc.

Les recherches menées en extraction d'information ont montré l'importance de certaines unités, telles que les noms de personnes, de lieux et d’organisations, les dates ou les montants. Le traitement de ces éléments, les « entités nommées », a donné lieu au développement d'algorithmes et de ressources utilisées par les systèmes informatiques.

Théorique et pratique, cet ouvrage propose des outils pour définir ces entités, les identifier, les lier à des bases de connaissance ou pour procéder à l’évaluation des systèmes.
 
 
Sommaire

1. Les entités nommées pour l’accès à l’information
2. Les entités nommées, des unités référentielles
3. Ressources autour des entités nommées
4. Reconnaître les entités nommées
5. Lier les entités nommées aux référentiels
6. Évaluation de la reconnaissance des entités nommées

168 pages - Octobre 2015
Ouvrage papier - broché 
ISBN 978-1-78405-104-4
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5-1-6R.Fuchs, 'Speech Rhythm in Varieties of English' , Springer

R.Fuchs,  'Speech Rhythm in Varieties of English' has appeared with Springer, in the 'Prosody, Phonology and Phonetics' series: https://www.springer.com/gp/book/9783662478172

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5-1-7Pejman Mowlaee et al., 'Phase-Aware Signal Processing in Speech Communication: Theory and Practice', Wiley 2016

Phase-Aware Signal Processing in Speech Communication: Theory and Practice

Pejman Mowlaee, Johannes Stahl, Josef Kulmer, Florian Mayer

http://eu.wiley.com/WileyCDA/WileyTitle/productCd-1119238811.html

An overview on the challenging new topic of phase-aware signal processing

Speech communication technology is a key factor in human-machine interaction, digital hearing aids, mobile telephony, and automatic speech/speaker recognition. With the proliferation of these applications, there is a growing requirement for advanced methodologies that can push the limits of the conventional solutions relying on processing the signal magnitude spectrum.

Single-Channel Phase-Aware Signal Processing in Speech Communication provides a comprehensive guide to phase signal processing and reviews the history of phase importance in the literature, basic problems in phase processing, fundamentals of phase estimation together with several applications to demonstrate the usefulness of phase processing.

Key features:

  • Analysis of recent advances demonstrating the positive impact of phase-based processing in pushing the limits of conventional methods.
  • Offers unique coverage of the historical context, fundamentals of phase processing and provides several examples in speech communication.
  • Provides a detailed review of many references and discusses the existing signal processing techniques required to deal with phase information in different applications involved with speech.
  • The book supplies various examples and MATLAB® implementations delivered within the PhaseLab toolbox.

Single-Channel Phase-Aware Signal Processing in Speech Communication is a valuable single-source for students, non-expert DSP engineers, academics and graduate students.

ejman Mowlaee, Johannes Stahl, Josef Kulmer, Florian Mayer
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5-2 Database
5-2-1ELRA - Language Resources Catalogue - Update (September 2017)
ELRA - Language Resources Catalogue - Update
-------------------------------------------------------

We are happy to announce that 2 new Monolingual Lexicons are now available in our catalogue. 

ELRA-L0098 Arabic dictionary of inflected words
ISLRN: 049-623-948-389-2

This dictionary consists of a list of 6 million inflected forms, fully vowelized, and tagged with grammatical information which includes POS and grammatical features, including number, gender, case, definiteness, tense, mood and compatibility with clitic agglutination. The data is formatted in conformity with the data formats of Unitex/GramLab.
This dictionary is also available together with recognition of agglutinated clitics and inflection system in the ELRA Catalogue under reference ELRA-L0099.
For more information, see: http://catalog.elra.info/product_info.php?products_id=1310


ELRA-L0099 Arabic dictionary of inflected words with recognition of agglutinated clitics and inflection system
This dictionary consists of 6 million inflected forms, fully vowelized, generated in compliance with the grammatical rules of Arabic and tagged with grammatical information which includes POS and grammatical features, including number, gender, case, definiteness, tense, mood and compatibility with clitic agglutination. It is accompanied by a grammatical resource that recognizes hundreds of millions of valid agglutinated words. In order to be able to update the full-form dictionary, a dictionary of 65 000 lemmas and the data required to inflect them and regenerate the full-form dictionary are also provided. The data is formatted in conformity with the data formats of Unitex/GramLab.
This dictionary is also available without recognition of agglutinated clitics and without inflection system in the ELRA Catalogue under reference ELRA-L0098.
For more information, see: http://catalog.elra.info/product_info.php?products_id=1311

For more information on the catalogue, please contact Valérie Mapelli mailto:mapelli@elda.org

If you would like to enquire about having your resources distributed by ELRA, please do not hesitate to contact us.

Visit our On-line Catalogue: http://catalog.elra.info
Visit the Universal Catalogue: http://universal.elra.info
Archives of ELRA Language Resources Catalogue Updates: http://www.elra.info/en/catalogues/language-resources-announcements/



 

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5-2-2Appen ButlerHill

 

Appen ButlerHill 

A global leader in linguistic technology solutions

RECENT CATALOG ADDITIONS—MARCH 2012

1. Speech Databases

1.1 Telephony

1.1 Telephony

Language

Database Type

Catalogue Code

Speakers

Status

Bahasa Indonesia

Conversational

BAH_ASR001

1,002

Available

Bengali

Conversational

BEN_ASR001

1,000

Available

Bulgarian

Conversational

BUL_ASR001

217

Available shortly

Croatian

Conversational

CRO_ASR001

200

Available shortly

Dari

Conversational

DAR_ASR001

500

Available

Dutch

Conversational

NLD_ASR001

200

Available

Eastern Algerian Arabic

Conversational

EAR_ASR001

496

Available

English (UK)

Conversational

UKE_ASR001

1,150

Available

Farsi/Persian

Scripted

FAR_ASR001

789

Available

Farsi/Persian

Conversational

FAR_ASR002

1,000

Available

French (EU)

Conversational

FRF_ASR001

563

Available

French (EU)

Voicemail

FRF_ASR002

550

Available

German

Voicemail

DEU_ASR002

890

Available

Hebrew

Conversational

HEB_ASR001

200

Available shortly

Italian

Conversational

ITA_ASR003

200

Available shortly

Italian

Voicemail

ITA_ASR004

550

Available

Kannada

Conversational

KAN_ASR001

1,000

In development

Pashto

Conversational

PAS_ASR001

967

Available

Portuguese (EU)

Conversational

PTP_ASR001

200

Available shortly

Romanian

Conversational

ROM_ASR001

200

Available shortly

Russian

Conversational

RUS_ASR001

200

Available

Somali

Conversational

SOM_ASR001

1,000

Available

Spanish (EU)

Voicemail

ESO_ASR002

500

Available

Turkish

Conversational

TUR_ASR001

200

Available

Urdu

Conversational

URD_ASR001

1,000

Available

1.2 Wideband

Language

Database Type

Catalogue Code

Speakers

Status

English (US)

Studio

USE_ASR001

200

Available

French (Canadian)

Home/ Office

FRC_ASR002

120

Available

German

Studio

DEU_ASR001

127

Available

Thai

Home/Office

THA_ASR001

100

Available

Korean

Home/Office

KOR_ASR001

100

Available

2. Pronunciation Lexica

Appen Butler Hill has considerable experience in providing a variety of lexicon types. These include:

Pronunciation Lexica providing phonemic representation, syllabification, and stress (primary and secondary as appropriate)

Part-of-speech tagged Lexica providing grammatical and semantic labels

Other reference text based materials including spelling/mis-spelling lists, spell-check dictionar-ies, mappings of colloquial language to standard forms, orthographic normalization lists.

Over a period of 15 years, Appen Butler Hill has generated a significant volume of licensable material for a wide range of languages. For holdings information in a given language or to discuss any customized development efforts, please contact: sales@appenbutlerhill.com

3. Named Entity Corpora

Language

Catalogue Code

Words

Description

Arabic

ARB_NER001

500,000

These NER Corpora contain text material from a vari-ety of sources and are tagged for the following Named Entities: Person, Organization, Location, Na-tionality, Religion, Facility, Geo-Political Entity, Titles, Quantities

English

ENI_NER001

500,000

Farsi/Persian

FAR_NER001

500,000

Korean

KOR_NER001

500,000

Japanese

JPY_NER001

500,000

Russian

RUS_NER001

500,000

Mandarin

MAN_NER001

500,000

Urdu

URD_NER001

500,000

3. Named Entity Corpora

Language

Catalogue Code

Words

Description

Arabic

ARB_NER001

500,000

These NER Corpora contain text material from a vari-ety of sources and are tagged for the following Named Entities: Person, Organization, Location, Na-tionality, Religion, Facility, Geo-Political Entity, Titles, Quantities

English

ENI_NER001

500,000

Farsi/Persian

FAR_NER001

500,000

Korean

KOR_NER001

500,000

Japanese

JPY_NER001

500,000

Russian

RUS_NER001

500,000

Mandarin

MAN_NER001

500,000

Urdu

URD_NER001

500,000

4. Other Language Resources

Morphological Analyzers – Farsi/Persian & Urdu

Arabic Thesaurus

Language Analysis Documentation – multiple languages

 

For additional information on these resources, please contact: sales@appenbutlerhill.com

5. Customized Requests and Package Configurations

Appen Butler Hill is committed to providing a low risk, high quality, reliable solution and has worked in 130+ languages to-date supporting both large global corporations and Government organizations.

We would be glad to discuss to any customized requests or package configurations and prepare a cus-tomized proposal to meet your needs.

6. Contact Information

Prithivi Pradeep

Business Development Manager

ppradeep@appenbutlerhill.com

+61 2 9468 6370

Tom Dibert

Vice President, Business Development, North America

tdibert@appenbutlerhill.com

+1-315-339-6165

                                                         www.appenbutlerhill.com

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5-2-3OFROM 1er corpus de français de Suisse romande
Nous souhaiterions vous signaler la mise en ligne d'OFROM, premier corpus de français parlé en Suisse romande. L'archive est, dans version actuelle, d'une durée d'environ 15 heures. Elle est transcrite en orthographe standard dans le logiciel Praat. Un concordancier permet d'y effectuer des recherches, et de télécharger les extraits sonores associés aux transcriptions. 
 
Pour accéder aux données et consulter une description plus complète du corpus, nous vous invitons à vous rendre à l'adresse suivante : http://www.unine.ch/ofrom
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5-2-4Real-world 16-channel noise recordings

We are happy to announce the release of DEMAND, a set of real-world
16-channel noise recordings designed for the evaluation of microphone
array processing techniques.

http://www.irisa.fr/metiss/DEMAND/

1.5 h of noise data were recorded in 18 different indoor and outdoor
environments and are available under the terms of the Creative Commons Attribution-ShareAlike License.

Joachim Thiemann (CNRS - IRISA)
Nobutaka Ito (University of Tokyo)
Emmanuel Vincent (Inria Nancy - Grand Est)

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5-2-5Aide à la finalisation de corpus oraux ou multimodaux pour diffusion, valorisation et dépôt pérenne

Aide à la finalisation de corpus oraux ou multimodaux pour diffusion, valorisation et dépôt pérenne

 

 

Le consortium IRCOM de la TGIR Corpus et l’EquipEx ORTOLANG s’associent pour proposer une aide technique et financière à la finalisation de corpus de données orales ou multimodales à des fins de diffusion et pérennisation par l’intermédiaire de l’EquipEx ORTOLANG. Cet appel ne concerne pas la création de nouveaux corpus mais la finalisation de corpus existants et non-disponibles de manière électronique. Par finalisation, nous entendons le dépôt auprès d’un entrepôt numérique public, et l’entrée dans un circuit d’archivage pérenne. De cette façon, les données de parole qui ont été enrichies par vos recherches vont pouvoir être réutilisées, citées et enrichies à leur tour de manière cumulative pour permettre le développement de nouvelles connaissances, selon les conditions d’utilisation que vous choisirez (sélection de licences d’utilisation correspondant à chacun des corpus déposés).

 

Cet appel d’offre est soumis à plusieurs conditions (voir ci-dessous) et l’aide financière par projet est limitée à 3000 euros. Les demandes seront traitées dans l’ordre où elles seront reçues par l’ IRCOM. Les demandes émanant d’EA ou de petites équipes ne disposant pas de support technique « corpus » seront traitées prioritairement. Les demandes sont à déposer du 1er septembre 2013 au 31 octobre 2013. La décision de financement relèvera du comité de pilotage d’IRCOM. Les demandes non traitées en 2013 sont susceptibles de l’être en 2014. Si vous avez des doutes quant à l’éligibilité de votre projet, n’hésitez pas à nous contacter pour que nous puissions étudier votre demande et adapter nos offres futures.

 

Pour palier la grande disparité dans les niveaux de compétences informatiques des personnes et groupes de travail produisant des corpus, L’ IRCOM propose une aide personnalisée à la finalisation de corpus. Celle-ci sera réalisée par un ingénieur IRCOM en fonction des demandes formulées et adaptées aux types de besoin, qu’ils soient techniques ou financiers.

 

Les conditions nécessaires pour proposer un corpus à finaliser et obtenir une aide d’IRCOM sont :

  • Pouvoir prendre toutes décisions concernant l’utilisation et la diffusion du corpus (propriété intellectuelle en particulier).

  • Disposer de toutes les informations concernant les sources des corpus et le consentement des personnes enregistrées ou filmées.

  • Accorder un droit d’utilisation libre des données ou au minimum un accès libre pour la recherche scientifique.

 

Les demandes peuvent concerner tout type de traitement : traitements de corpus quasi-finalisés (conversion, anonymisation), alignement de corpus déjà transcrits, conversion depuis des formats « traitement de textes », digitalisation de support ancien. Pour toute demande exigeant une intervention manuelle importante, les demandeurs devront s’investir en moyens humains ou financiers à la hauteur des moyens fournis par IRCOM et ORTOLANG.

 

IRCOM est conscient du caractère exceptionnel et exploratoire de cette démarche. Il convient également de rappeler que ce financement est réservé aux corpus déjà largement constitués et ne peuvent intervenir sur des créations ex-nihilo. Pour ces raisons de limitation de moyens, les propositions de corpus les plus avancés dans leur réalisation pourront être traitées en priorité, en accord avec le CP d’IRCOM. Il n’y a toutefois pas de limite « théorique » aux demandes pouvant être faites, IRCOM ayant la possibilité de rediriger les demandes qui ne relèvent pas de ses compétences vers d’autres interlocuteurs.

 

Les propositions de réponse à cet appel d’offre sont à envoyer à ircom.appel.corpus@gmail.com. Les propositions doivent utiliser le formulaire de deux pages figurant ci-dessous. Dans tous les cas, une réponse personnalisée sera renvoyée par IRCOM.

 

Ces propositions doivent présenter les corpus proposés, les données sur les droits d’utilisation et de propriétés et sur la nature des formats ou support utilisés.

 

Cet appel est organisé sous la responsabilité d’IRCOM avec la participation financière conjointe de IRCOM et l’EquipEx ORTOLANG.

 

Pour toute information complémentaire, nous rappelons que le site web de l'Ircom (http://ircom.corpus-ir.fr) est ouvert et propose des ressources à la communauté : glossaire, inventaire des unités et des corpus, ressources logicielles (tutoriaux, comparatifs, outils de conversion), activités des groupes de travail, actualités des formations, ...

L'IRCOM invite les unités à inventorier leur corpus oraux et multimodaux - 70 projets déjà recensés - pour avoir une meilleure visibilité des ressources déjà disponibles même si elles ne sont pas toutes finalisées.

 

Le comité de pilotage IRCOM

 

 

Utiliser ce formulaire pour répondre à l’appel : Merci.

 

Réponse à l’appel à la finalisation de corpus oral ou multimodal

 

Nom du corpus :

 

Nom de la personne à contacter :

Adresse email :

Numéro de téléphone :

 

Nature des données de corpus :

 

Existe-t’il des enregistrements :

Quel média ? Audio, vidéo, autre…

Quelle est la longueur totale des enregistrements ? Nombre de cassettes, nombre d’heures, etc.

Quel type de support ?

Quel format (si connu) ?

 

Existe-t’il des transcriptions :

Quel format ? (papier, traitement de texte, logiciel de transcription)

Quelle quantité (en heures, nombre de mots, ou nombre de transcriptions) ?

 

Disposez vous de métadonnées (présentation des droits d’auteurs et d’usage) ?

 

Disposez-vous d’une description précise des personnes enregistrées ?

 

Disposez-vous d’une attestation de consentement éclairé pour les personnes ayant été enregistrées ? En quelle année (environ) les enregistrements ont eu lieu ?

 

Quelle est la langue des enregistrements ?

 

Le corpus comprend-il des enregistrements d’enfants ou de personnes ayant un trouble du langage ou une pathologie ?

Si oui, de quelle population s’agit-il ?

 

 

Dans un souci d’efficacité et pour vous conseiller dans les meilleurs délais, il nous faut disposer d’exemples des transcriptions ou des enregistrements en votre possession. Nous vous contacterons à ce sujet, mais vous pouvez d’ores et déjà nous adresser par courrier électronique un exemple des données dont vous disposez (transcriptions, métadonnées, adresse de page web contenant les enregistrements).

 

Nous vous remercions par avance de l’intérêt que vous porterez à notre proposition. Pour toutes informations complémentaires veuillez contacter Martine Toda martine.toda@ling.cnrs.fr ou à ircom.appel.corpus@gmail.com.

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5-2-6Rhapsodie: un Treebank prosodique et syntaxique de français parlé

Rhapsodie: un Treebank prosodique et syntaxique de français parlé

 

Nous avons le plaisir d'annoncer que la ressource Rhapsodie, Corpus de français parlé annoté pour la prosodie et la syntaxe, est désormais disponible sur http://www.projet-rhapsodie.fr/

 

Le treebank Rhapsodie est composé de 57 échantillons sonores (5 minutes en moyenne, au total 3h de parole, 33000 mots) dotés d’une transcription orthographique et phonétique alignées au son.

 

Il s'agit d’une ressource de français parlé multi genres (parole privée et publique ; monologues et dialogues ; entretiens en face à face vs radiodiffusion, parole plus ou moins interactive et plus ou moins planifiée, séquences descriptives, argumentatives, oratoires et procédurales) articulée autour de sources externes (enregistrements extraits de projets antérieurs, en accord avec les concepteurs initiaux) et internes. Nous tenons en particulier à remercier les responsables des projets CFPP2000, PFC, ESLO, C-Prom ainsi que Mathieu Avanzi, Anne Lacheret, Piet Mertens et Nicolas Obin.

 

Les échantillons sonores (wave & MP3, pitch nettoyé et lissé), les transcriptions orthographiques (txt), les annotations macrosyntaxiques (txt), les annotations prosodiques (xml, textgrid) ainsi que les metadonnées (xml & html) sont téléchargeables librement selon les termes de la licence Creative Commons Attribution - Pas d’utilisation commerciale - Partage dans les mêmes conditions 3.0 France.

Les annotations microsyntaxiques seront disponibles prochainement

 Les métadonnées sont également explorables en ligne grâce à un browser.

 Les tutoriels pour la transcription, les annotations et les requêtes sont disponibles sur le site Rhapsodie.

 Enfin, L’annotation prosodique est interrogeable en ligne grâce au langage de requêtes Rhapsodie QL.

 L'équipe Ressource Rhapsodie (Modyco, Université Paris Ouest Nanterre)

Sylvain Kahane, Anne Lacheret, Paola Pietrandrea, Atanas Tchobanov, Arthur Truong.

 Partenaires : IRCAM (Paris), LATTICE (Paris), LPL (Aix-en-Provence), CLLE-ERSS (Toulouse).

 

********************************************************

Rhapsodie: a Prosodic and Syntactic Treebank for Spoken French

We are pleased to announce that Rhapsodie, a syntactic and prosodic treebank of spoken French created with the aim of modeling the interface between prosody, syntax and discourse in spoken French is now available at   http://www.projet-rhapsodie.fr/

The Rhapsodie treebank is made up of 57 short samples of spoken French (5 minutes long on average, amounting to 3 hours of speech and a 33 000 word corpus) endowed with an orthographical phoneme-aligned transcription . 

The corpus is representative of different genres (private and public speech; monologues and dialogues; face-to-face interviews and broadcasts; more or less interactive discourse; descriptive, argumentative and procedural samples, variations in planning type).

The corpus samples have been mainly drawn from existing corpora of spoken French and partially created within the frame of theRhapsodie project. We would especially like to thank the coordinators of the  CFPP2000, PFC, ESLO, C-Prom projects as well as Piet Mertens, Mathieu Avanzi, Anne Lacheret and Nicolas Obin.

The sound samples (waves, MP3, cleaned and stylized pitch), the orthographic transcriptions (txt), the macrosyntactic annotations (txt), the prosodic annotations  (xml, textgrid) as well as the metadata (xml and html) can be freely downloaded under the terms of the Creative Commons licence Attribution - Noncommercial - Share Alike 3.0 France.

Microsyntactic annotation will be available soon.

The metadata are  searchable on line through a browser.

The prosodic annotation can be explored on line through the Rhapsodie Query Language.

The tutorials of transcription, annotations and Rhapsodie Query Language  are available on the site.

 

The Rhapsodie team (Modyco, Université Paris Ouest Nanterre :

Sylvain Kahane, Anne Lacheret, Paola Pietrandrea, Atanas Tchobanov, Arthur Truong.

Partners: IRCAM (Paris), LATTICE (Paris), LPL (Aix-en-Provence),CLLE-ERSS (Toulouse).

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5-2-7Annotation of “Hannah and her sisters” by Woody Allen.

We have created and made publicly available a dense audio-visual person-oriented ground-truth annotation of a feature movie (100 minutes long): “Hannah and her sisters” by Woody Allen.

The annotation includes

•          Face tracks in video (densely annotated, i.e., in each frame, and person-labeled)

•             Speech segments in audio (person-labeled)

•             Shot boundaries in video



The annotation can be useful for evaluating



•   Person-oriented video-based tasks (e.g., face tracking, automatic character naming, etc.)

•             Person-oriented audio-based tasks (e.g., speaker diarization or recognition)

•             Person-oriented multimodal-based tasks (e.g., audio-visual character naming)



Detail on Hannah dataset and access to it can be obtained there:

https://research.technicolor.com/rennes/hannah-home/

https://research.technicolor.com/rennes/hannah-download/



Acknowledgments:

This work is supported by AXES EU project: http://www.axes-project.eu/










Alexey Ozerov Alexey.Ozerov@technicolor.com

Jean-Ronan Vigouroux,

Louis Chevallier

Patrick Pérez

Technicolor Research & Innovation



 

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5-2-8French TTS

Text to         Speech Synthesis:
      over an hour of speech       synthesis samples from         1968 to 2001 by       25 French, Canadian, US , Belgian,       Swedish, Swiss systems
     
     
33 ans de synthèse de la parole à         partir du texte: une promenade sonore (1968-2001)
        (33 years of
Text to Speech Synthesis       in French : an audio tour (1968-2001)       )
      Christophe d'Alessandro
      Article published in         Volume 42 - No. 1/2001 issue of 
Traitement       Automatique des Langues  (TAL,       Editions Hermes),         pp. 297-321.
     
      posted to:
      http://groupeaa.limsi.fr/corpus:synthese:start

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5-2-9Google 's Language Model benchmark
 Here is a brief description of the project.

'The purpose of the project is to make available a standard training and test setup for language modeling experiments.

The training/held-out data was produced from a download at statmt.org using a combination of Bash shell and Perl scripts distributed here.

This also means that your results on this data set are reproducible by the research community at large.

Besides the scripts needed to rebuild the training/held-out data, it also makes available log-probability values for each word in each of ten held-out data sets, for each of the following baseline models:

  • unpruned Katz (1.1B n-grams),
  • pruned Katz (~15M n-grams),
  • unpruned Interpolated Kneser-Ney (1.1B n-grams),
  • pruned Interpolated Kneser-Ney (~15M n-grams)

 

Happy benchmarking!'

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5-2-10International Standard Language Resource Number (ISLRN) (ELRA Press release)

Press Release - Immediate - Paris, France, December 13, 2013

Establishing the International Standard Language Resource Number (ISLRN)

12 major NLP organisations announce the establishment of the ISLRN, a Persistent Unique Identifier, to be assigned to each Language Resource.

On November 18, 2013, 12 NLP organisations have agreed to announce the establishment of the International Standard Language Resource Number (ISLRN), a Persistent Unique Identifier, to be assigned to each Language Resource. Experiment replicability, an essential feature of scientific work, would be enhanced by such unique identifier. Set up by ELRA, LDC and AFNLP/Oriental-COCOSDA, the ISLRN Portal will provide unique identifiers using a standardised nomenclature, as a service free of charge for all Language Resource providers. It will be supervised by a steering committee composed of representatives of participating organisations and enlarged whenever necessary.

More information on ELRA and the ISLRN, please contact: Khalid Choukri choukri@elda.org

More information on ELDA, please contact: Hélène Mazo mazo@elda.org

ELRA

55-57, rue Brillat Savarin

75013 Paris (France)

Tel.: +33 1 43 13 33 33

Fax: +33 1 43 13 33 30

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5-2-11ISLRN new portal
Opening of the ISLRN Portal
ELRA, LDC,  and AFNLP/Oriental-COCOSDA announce the opening of the ISLRN Portal @ www.islrn.org.


Further to the establishment of the International Standard Language Resource Number (ISLRN) as a unique and universal identification schema for Language Resources on November 18, 2013, ELRA, LDC and AFNLP/Oriental-COCOSDA now announce the opening of the ISLRN Portal (www.islrn.org). As a service free of charge for all Language Resource providers and under the supervision of a steering committee composed of representatives of participating organisations, the ISLRN Portal provides unique identifiers using a standardised nomenclature.

Overview
The 13-digit ISLRN format is: XXX-XXX-XXX-XXX-X. It can be allocated to any Language Resource; its composition is neutral and does not include any semantics in reference to the type or nature of the Language Resource. The ISLRN is a randomly created number with a check digit that validates a Verhoeff algorithm.

Two types of external players may interact with the ISLRN Portal: Visitors and Providers. Visitors may browse the web site and search for the ISLRN of a given Language Resource by its name or by its number if it exists. Providers are registered and own credentials. They can request a new ISLRN for a given Language Resource. A provider has the possibility to become certified, after moderation, in order to be able to import metadata in XML format.

The functionalities that can be accessed by Visitors are:

-          Identify a language resource according to its ISLRN
-          Identify an ISLRN by the name of a language resource
-          Get information about ISLRN, FAQ, Basic Metadata, Legal Information
-          View last 5 accepted resources (“What’s new” block on home page)
-          Sign up to become a provider

The functionalities that can be accessed by Providers, once they have signed up, are:

-          Log in
-          Request an ISLRN according to the metadata of a given resource
-          Request to become a certified provider so as to import XML files containing metadata
-          Import one or more metadata descriptions in XML to request ISLRN(s) (only for certified providers)
-          Edit pending requests
-          Access previous requests
-          Contact a Moderator or an Administrator
-          Edit Providers’ own profile

ISLRN request is handled by moderators within 5 working days.
Contact: islrn@elda.org

Background
The International Standard Language Resource Number (ISLRN) is a unique and universal identification schema for Language Resources which provides Language Resources with unique identifier using a standardised nomenclature. It also ensures that Language Resources are correctly identified, and consequently, recognised with proper references for their usage in applications in R&D projects, products evaluation and benchmark as well as in documents and scientific papers. Moreover, it is a major step in the interconnected world that Human Language Technologies (HLT) has become: unique resources must be identified as they are and meta-catalogues need a common identification format to manage data correctly.

The ISLRN does not intend to replace local and specific identifiers, it is not meant to be a legal deposit, not an obligation, but rather an essential and best practice. For instance a resource that is distributed by several data centres will still have the “local” data-centre identifier but will have a unique ISLRN.

********************************************************************
About ELRA
The European Language Resources Association (ELRA) is a non-profit making organisation founded by the European Commission in 1995, with the mission of providing a clearing house for language resources and promoting Human Language Technologies (HLT). To find out more about ELRA, please visit www.elra.info.

About LDC
Founded in 1992, the Linguistic Data Consortium (LDC) is an open consortium of universities, companies and government research laboratories. It creates, collects and distributes speech and text databases, lexicons, and other resources for research and development purposes. The University of Pennsylvania is the LDC's host institution. To find out more about LDC, please visit www.ldc.upenn.edu.

About AFNLP
The mission of the Asian Federation of Natural Language Processing (AFNLP) is to promote and enhance R&D relating to the computational analysis and the automatic processing of all languages of importance to the Asian region by assisting and supporting like-minded organizations and institutions through information sharing, conference organization, research and publication co-ordination, and other forms of support. To find out more about AFNLP, please visit www.afnlp.org.

About Oriental-COCOSDA
The International Committee for the Co-ordination and Standardisation of Speech Databases and Assesment Techniques, Oriental-COCOSDA, has been established to encourage and promote international interaction and cooperation in the foundation areas of Spoken Language Processing, especially for Speech Input/Output. To find out more about Oriental-COCOSDA, please visit our web site: www.cocosda.org

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5-2-12Speechocean – update (January 2017)

 

Speechocean – update (Jan 2017):

 

 

 

Speechocean: A global language resources and data services supplier

 

 

 

About Speechocean

 

Speechocean is one of the world well-known language related resources & services provider in the fields of Human Computer Interaction and Human Language Technology. At present, we can provide data services with 110+ languages and dialects across the world.

 

 

 

KingLine Data Center ---Data Sharing Platform

 

Kingline Data Center is operated and supervised by Speechocean, which is mainly focused on language resources creating and providing for research and development of human language technology.

 

These diversified corpora are widely used for the research and development in the fields of Speech Recognition, Speech Synthesis, Natural Language Processing, Machine Translation, Web Search, etc. All corpora are openly accessible for users all over the world, including users from scientific research institutions, enterprises or individuals.

 

For more detailed information, please visit our website: http://kingline.speechocean.com

 

 

 

New released corpora:

 

  1. Uighur Speech Recognition Corpus-Sentence/Conversation (Telephone)-300 Speakers

 

ID: King-ASR-450

 

The Uighur Telephone Speech Recognition Corpus was collected in China. It contains the voices of 300 different speakers (150 males, 150 females) who were balanced distributed in age (mainly 18-35, 36-45, >46), gender and regional accents (for the details, please see the technical document). The script contains 120,000(approx.) utterances in total (for more details of script structure design, please check the specification), specially designed to provide materials for both training and testing of many classes of speech recognizers. Each speaker was recorded in quiet environments (home/office). Telephone platform, i.e. IVR was used for speech collection. Each utterance wave was stored in a separate file and uncompressed. A pronunciation lexicon is available. All audio files were manually transcribed and annotated by native transcribers. Details are available with specification.

 

 

 

  1. Hindi Speech Recognition Corpus- Conversation (Mobile)- 200 Speakers

 

ID: King-ASR-323

 

The Hindi Mobile Speech Recognition Corpus was collected in India. It contains the voices of 200 different speakers (108 males, 92 females) who were balanced distributed in age (16-30, 31-45, 46-60), gender and regional accents (for the details, please see the technical document). More than 20 topics were included in total (for more details of script structure design, please check the specification), specially designed to provide materials for both training and testing of many classes of speech recognizers. Each speaker was recorded in a quiet office environment. Mobile platforms, i.e. iOS, Android and Windows were used for speech collection. Each utterance wave was stored in a separate file and uncompressed. A pronunciation lexicon is available with a phonemic transcription in SAMPA. All manually checked. All audio files were manually transcribed and annotated by native transcribers. Details are available with specification.

 

 

 

  1. Kids Mandarin Speech Recognition Corpus-Sentence (Mobile, Desktop & Smart TV)-575 Speakers

 

ID: King-ASR-409

 

The Kids Mandarin Speech Recognition Corpus was collected in China Liaoning Province and Hebei Province. It contains the voices of 575 different native speakers (283 males, 292 females) who were balanced distributed in age (4-9 years old), gender and regional accents (for the details, please see the technical document). The script contains 396,000(approx.) utterances in total( for more details of script structure design, please check the specification), specially designed to provide material for both training and testing of many classes of speech recognizers. Each speaker was recorded in a quiet office room. Mobile phone, desktop and smart TV were used for speech collection. Each utterance wave is stored in a separate file and uncompressed. A pronunciation lexicon is available with a phonemic transcription in Pinyin. All manually checked. All audio files were manually transcribed and annotated by native transcribers. Details are available with specification.

 

 

 

  1. Hong Kong English Speech Recognition Corpus-Sentence (Mobile)-200 Speakers

 

ID: King-ASR-287

 

The Hong Kong English Mobile Speech Recognition Corpus was collected in Hong Kong. It contains the voices of 200 different speakers (99 males, 101 females) who were balanced distributed in age (18-30, 31-45, 46-60), gender and regional accents (for the details, please see the technical document). The script contains 179,406(approx.) utterances in total (for more details of script structure design, please check the specification), specially designed to provide materials for both training and testing of many classes of speech recognizers. Each speaker was recorded in a quiet environment. Mobile platforms, i.e. iOSAndroidWindows were used for speech collection. Each utterance wave was stored in a separate file and uncompressed. A pronunciation lexicon is available with a phonemic transcription in Hepburn. All manually checked. All audio files were manually transcribed and annotated by native transcribers. Details are available with specification.

 

 

 

Contact Information

 

Xianfeng Cheng

 

VP

 

Tel: +86-10-62660928; +86-10-62660053 ext.8080

 

Mobile: +86 13681432590

 

Skype: xianfeng.cheng1

 

Email: chengxianfeng@speechocean.com; cxfxy0cxfxy0@gmail.com

 

Website: www.speechocean.com


 

 

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5-2-13kidLUCID: London UCL Children’s Clear Speech in Interaction Database

kidLUCID: London UCL Children’s Clear Speech in Interaction Database

We are delighted to announce the availability of a new corpus of spontaneous speech for children aged 9 to 14 years inclusive, produced as part of the ESRC-funded project on ‘Speaker-controlled Variability in Children's Speech in Interaction’ (PI: Valerie Hazan).

Speech recordings (a total of 288 conversations) are available for 96 child participants (46M, 50F, range 9;0 to 15;0 years), all native southern British English speakers. Participants were recorded in pairs while completing the diapix spot-the-difference picture task in which the pair verbally compared two scenes, only one of which was visible to each talker. High-quality digital recordings were made in sound-treated rooms. For each conversation, a stereo audio recording is provided with each speaker on a separate channel together with a Praat Textgrid containing separate word- and phoneme-level segmentations for each speaker.

There are six recordings per speaker pair made in the following conditions:

  • NOB (No barrier): both speakers heard each other normally

  • VOC (Vocoder): one conversational partner heard the other's speech after it had been processed in real time through a noise-excited three channel vocoder

  • BAB (Babble): one conversational partner heard the other's speech in a background of adult multi-talker babble at an approximate SNR of 0 dB.

The kidLUCID corpus is available online within the OSCAAR (Online Speech/Corpora Archive and Analysis Resource) archive (https://oscaar.ci.northwestern.edu/). Free access can be requested for research purposes. Further information about the project can be found at: http://www.ucl.ac.uk/pals/research/shaps/research/shaps/research/clear-speech-strategies

This work was supported by Economic and Social Research Council Grant No. RES-062- 23-3106.

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5-2-14Robust speech datasets and ASR software tools


We are happy to announce the release of a table of 44 publicly available robust speech processing datasets and a table of 4 ASR software tools on the wiki of ISCA's Robust Speech Processing SIG:
https://wiki.inria.fr/rosp/Datasets#Speech_datasets
https://wiki.inria.fr/rosp/Software#Automatic_speech_recognition

We hope that these tables will promote wider dissemination of the datasets and software tools available in our community and help newcomers select the most suitable dataset or software for a given experiment. We plan to provide additional tables on, e.g., room impulse response datasets or speaker recognition software in the future.

We highly welcome your input, especially additional tables/entries and reproducible baselines for each dataset. It just takes a few minutes thanks to the simple wiki interface.

For more information about joining the SIG and contributing, see
https://wiki.inria.fr/rosp/

Jonathan Le Roux, Emmanuel Vincent, and Ramon Astudillo

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5-2-15International Standard Language Resource Number (ISLRN) implemented by ELRA and LDC

ELRA and LDC partner to implement ISLRN process and assign identifiers to all the Language Resources in their catalogues.

 

Following the meeting of the largest NLP organizations, the NLP12, and their endorsement of the International Standard Language Resource Number (ISLRN), ELRA and LDC partnered to implement the ISLRN process and to assign identifiers to all the Language Resources (LRs) in their catalogues. The ISLRN web portal was designed to enable the assignment of unique identifiers as a service free of charge for all Language Resource providers. To enhance the use of ISLRN, ELRA and LDC have collaborated to provide the ISLRN 13-digit ID to all the Language Resources distributed in their respective catalogues. Anyone who is searching the ELRA and LDC catalogues can see that each Language Resource is now identified by both the data centre ID and the ISLRN number. All providers and users of such LRs should refer to the latter in their own publications and whenever referring to the LR.

 

ELRA and LDC will continue their joint involvement in ISLRN through active participation in this web service.

 

Visit the ELRA and LDC catalogues, respectively at http://catalogue.elra.info and https://catalog.ldc.upenn.edu

 

Background

The International Standard Language Resource Number (ISLRN) aims to provide unique identifiers using a standardised nomenclature, thus ensuring that LRs are correctly identified, and consequently, recognised with proper references for their usage in applications within R&D projects, product evaluation and benchmarking, as well as in documents and scientific papers. Moreover, this is a major step in the networked and shared world that Human Language Technologies (HLT) has become: unique resources must be identified as such and meta-catalogues need a common identification format to manage data correctly.

The ISLRN portal can be accessed from http://www.islrn.org,

 

***About NLP12***

Representatives of the major Natural Language Processing and Computational Linguistics organizations met in Paris on 18 November 2013 to harmonize and coordinate their activities within the field.
The results of this coordination are expressed in the Paris Declaration: http://www.elra.info/NLP12-Paris-Declaration.html.

 

*** About ELRA ***
The European Language Resources Association (ELRA) is a non-profit making organisation founded by the European Commission in 1995, with the mission of providing a clearing house for language resources and promoting Human Language Technologies (HLT).
To find out more about ELRA, please visit our web site: http://www.elra.info

*** About LDC ***

The Linguistic Data Consortium (LDC) is an open consortium of universities, libraries, corporations and research laboratories that creates and distributes linguistic resources for language-related education, research and technology development.

To find out more about LDC, please visit our web site: https://www.ldc.upenn.edu


For more information, please contact: admin@islrn.org

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5-2-16Base de données LIBRE et GRATUITE pour la reconnaissance du locuteur
Je me permet de vous solliciter pour contribuer à la création 
d?une base de données LIBRE et GRATUITE
pour la reconnaissance du locuteur.

Plus de détails et la marche à suivre ci-dessous.

Merci beaucoup,
Anthony Larcher
 
 
 
Récemment, un certain nombre de laboratoires spécialisés dans la reconnaissance du locuteur dépendante du texte ont initié le projet RedDots.

Il s?agit d?une initiative volontaire sur financement propre des laboratoires.
Ce projet encourage des discussions sur les thèmes de la reconnaissance du locuteur,
la collection de corpus et les cas d?usage propres à cette technologie à travers un Google Group.

Dans le cadre du projet RedDots, l?Institute for Infocomm Research (Singapour) a développé une application Android 
qui permet d?enregistrer des données sur un téléphone portable.

Cette base de données a pour but de pallier certaines lacunes des corpus existants:
- le coût (certaines bases standard sont vendues à plusieurs milliers d?euro)
- la taille limitée (le nombre limité de locuteurs ne permet plus d?évaluer les systèmes de reconnaissance de manière significative)
- la variabilité limitée (les données sont actuellement enregistrées dans plus de 5 pays dans le monde entier)

Afin de distributer une base de données, qui puisse bénéficier librement 
à l?ensemble de la communauté de recherche nous vous sollicitons.
 
 
Comment faire et en combien de temps?
- inscrivez vous en 2 minutes à l?adresse suivante
- installez l?application Android sur votre téléphone en 2 minutes, saisissez l'ID et mot de passe qui vous seront envoyé par email
- enregistrez une session  3 minutes sur votre téléphone
 
Tout se fait en moins de 10 minutes?
Une des limitations principale des corpus existant est le nombre limité de sessions 
enregistrée par locuteur et le court intervalle de temps au cours duquel ces sessions sont enregistrées.
Afin de combler ce manque nous espérons que chaque participant acceptera d?enregistrer
plusieurs sessions dans les mois à venir.
Idealement, chaque participant enregistrera 3 ou 4 minutes par semaine pendant un an.
 
Ou vont mes données et pour quoi sont elles utilisées?
Les données sont actuellement envoyées sur un serveur de l?Institute for Infocomm Research 
à Singapour. Un institut de recherche public.
En vous enregistrant, vous acceptez que ces données soient utilisées à des fins de recherche
uniquement. ces données seront mise à disposition en ligne gratuitement tout au long du projet.

Merci pour votre contribution, n?hésitez pas à faire circuler cet email.
Plus de détails seront données prochainement dans un article soumis à INTERSPEECH 2015.

Anthony Larcher
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5-2-17Linguistic Data Consortium (LDC) update (August 2017)

 In this newsletter:

Fall 2017 LDC Data Scholarship program

LDC at Interspeech 2017



New Publications:

Multi-Language Conversational Telephone Speech 2011 -- South Asian

GALE Phase 4 Arabic Broadcast Conversation Speech

GALE Phase 4 Arabic Broadcast Conversation Transcripts

Fall 2017 LDC Data Scholarship program - September 15 deadline approaching

 

There is still time to apply to the Fall 2017 LDC Data Scholarship program. Applications will be accepted through Friday September 15, 2017. The LDC Data Scholarship program provides university students with access to LDC data at no cost. Students must complete an application which consists of a data use proposal and letter of support from their advisor.

For more information on application requirements and program rules, please visit the LDC Data Scholarship page. 

 

Applicants can email their materials to the LDC Data Scholarship program. 

 

LDC at Interspeech 2017

 

LDC will once again be exhibiting at Interspeech, held this year August 20-24 in Stockholm, Sweden. Stop by booth 17 to learn more about recent developments at the Consortium and new publications.

 

Also, be on the lookout for the following oral presentation by LDC:


Call My Net Corpus: A Multilingual Corpus for Evaluation of Speaker Recognition Technology 

Karen Jones, Stephanie Strassel, Kevin Walker, David Graff, Jonathan Wright

Wednesday, August 3, 17:40-18:00 in the Agula Magna room 

 

LDC will post conference updates via our Twitter feed and Facebook page. We hope to see you there!   


New publications:

(1) Multi-Language Conversational Telephone Speech 2011 -- South Asian was developed by LDC and is comprised of approximately 118 hours of telephone speech in five distinct language varieties of South Asia (i.e. the Indian sub-continent): Bengali, Hindi, Punjabi, Tamil and Urdu. The data were collected primarily to support research and technology evaluation in automatic language identification, and portions of these telephone calls were used in the NIST 2011 Language Recognition Evaluation (LRE). LRE 2011 focused on language pair discrimination for 24 languages/dialects, some which could be considered mutually intelligible or closely related.

Participants were recruited by native speakers who contacted acquaintances in their social network. Those native speakers made one call, up to 15 minutes, to each acquaintance. The data was collected using LDC's telephone collection infrastructure, comprised of three computer telephony systems. Human auditors labeled calls for callee gender, dialect type, and noise. Demographic information about the participants was not collected.

LDC has also released the following as part of the Multi-Language Conversation Telephone Speech 2011 series: Slavic Group (LDC2016S11)  and Turkish (LDC2017S09).

Multi-Language Conversational Telephone Speech 2011 -- South Asian is distributed via web download.

 

2017 Subscription Members will receive copies of this corpus. 2017 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for US $2,500.


*

(2) GALE Phase 4 Arabic Broadcast Conversation Speech was developed by LDC and is comprised of approximately 75 hours of Arabic broadcast conversation speech collected in 2008 and 2009 by LDC, MediaNet, Tunis, Tunisia and MTC, Rabat, Morocco during Phase 4 of the DARPA GALE (Global Autonomous Language Exploitation) Program.

 

Corresponding transcripts are released as GALE Phase 4 Arabic Broadcast Conversation Transcripts (LDC2017T12).

 

This release contains 83 audio files presented in FLAC-compressed Waveform Audio File format (.flac), 16000 Hz single-channel 16-bit PCM. Each file was audited by a native Arabic speaker following Audit Procedure Specification Version 2.0 which is included in this release. 

 

The broadcast conversation recordings in this release feature interviews, call-in programs and roundtable discussions focusing principally on current events from the following sources: Al Alam News Channel, based in Iran; Al Fayhaa, an Iraqi television channel; Al Hiwar, a regional broadcast station based in the United Kingdom; Alnurra, a U.S. government-funded regional broadcaster; Aljazeera, a regional broadcaster located in Doha, Qatar; Al Ordiniyah, a national broadcast station in Jordan; Dubai TV, a broadcast station in the United Arab Emirates; Lebanese Broadcasting Corporation, a Lebanese television station; Saudi TV, a national television station based in Saudi Arabia; Syria TV, the national television station in Syria; and Tunisian National TV, a national television station in Tunisia.

GALE Phase 4 Arabic Broadcast Conversation Speech is distributed via web download.

 

2017 Subscription Members will receive copies of this corpus. 2017 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for US $2,000.

*


(3) GALE Phase 4 Arabic Broadcast Conversation Transcripts was developed by LDC and contains transcriptions of approximately 75 hours of Arabic broadcast conversation speech collected in 2008 and 2009 by LDC, MediaNet, Tunis, Tunisia and MTC, Rabat, Morocco during Phase 4 of the DARPA GALE (Global Autonomous Language Exploitation) program.

 

Corresponding audio data is released as GALE Phase 4 Arabic Broadcast Conversation Speech (LDC2017S15).

 

The transcript files are in plain-text, tab-delimited format (TDF) with UTF-8 encoding, and the transcribed data totals 475,211 tokens. The files in this corpus were transcribed by LDC staff and/or by transcription vendors under contract to LDC. Transcribers followed LDC's quick transcription guidelines (QTR) and quick rich transcription specification (QRTR) both of which are included in the documentation with this release.

GALE Phase 4 Arabic Broadcast Conversation Transcripts is distributed via web download.

 

2017 Subscription Members will receive copies of this corpus. 2017 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for US $1,500.

Membership Office

Linguistic Data Consortium

University of Pennsylvania

T: +1-215-573-1275

E: ldc@ldc.upenn.edu

M: 3600 Market St. Suite 810

      Philadelphia, PA 19104

 

 

 

 

 











 

 

 

 

 

 

 

 

 


 

 

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5-2-18ISLRN adopted by Joint Research Center (JRC) of the European Commission

JRC, the EC's Joint Research Centre, an important LR player: First to adopt the ISLRN initiative

 

The Joint Research Centre (JRC), the European Commission's in house science service, is the first organisation to use the International Standard Language Resource Number (ISLRN) initiative and has requested ISLRN 13-digit unique identifiers to its Language Resources (LR).
Thus, anyone who is using JRC LRs may now refer to this number in their own publications.

 

The current JRC LRs (downloadable from https://ec.europa.eu/jrc/en/language-technologies) with an ISLRN ID are:

 

 

Background

The International Standard Language Resource Number (ISLRN) aims to provide unique identifiers using a standardised nomenclature, thus ensuring that LRs are correctly identified, and consequently, recognised with proper references for their usage in applications within R&D projects, product evaluation and benchmarking, as well as in documents and scientific papers. Moreover, this is a major step in the networked and shared world that Human Language Technologies (HLT) has become: unique resources must be identified as such and meta-catalogues need a common identification format to manage data correctly.
The ISLRN portal can be accessed from http://www.islrn.org,

 

*** About the JRC ***

As the Commission's in-house science service, the Joint Research Centre's mission is to provide EU policies with independent, evidence-based scientific and technical support throughout the whole policy cycle.
Within its research in the field of global security and crisis management, the JRC develops open source intelligence and analysis systems that can automatically harvest and analyse a huge amount of multi-lingual information from the internet-based sources. In this context, the JRC has developed Language Technology resources and tools that can be used for highly multilingual text analysis and cross-lingual applications.
To find out more about JRC's research in open source information monitoring, please visit https://ec.europa.eu/jrc/en/research-topic/internet-surveillance-systems. To access media monitoring applications directly, go to http://emm.newsbrief.eu/overview.html.

 

*** About ELRA ***
The European Language Resources Association (ELRA) is a non-profit making organisation founded by the European Commission in 1995, with the mission of providing a clearing house for language resources and promoting Human Language Technologies (HLT).
To find out more about ELRA, please visit our web site: http://www.elra.info

For more information, contact admin@ilsrn.org
 

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5-2-19Forensic database of voice recordings of 500+ Australian English speakers

Forensic database of voice recordings of 500+ Australian English speakers

We are pleased to announce that the forensic database of voice recordings of 500+ Australian English speakers is now published.

The database was collected by the Forensic Voice Comparison Laboratory, School of Electrical Engineering & Telecommunications, University of New South Wales as part of the Australian Research Council funded Linkage Project on making demonstrably valid and reliable forensic voice comparison a practical everyday reality in Australia. The project was conducted in partnership with: Australian Federal Police,  New South Wales Police,  Queensland Police, National Institute of Forensic Sciences, Australasian Speech Sciences and Technology Association, Guardia Civil, Universidad Autónoma de Madrid.

The database includes multiple non-contemporaneous recordings of most speakers. Each speaker is recorded in three different speaking styles representative of some common styles found in forensic casework. Recordings are recorded under high-quality conditions and extraneous noises and crosstalk have been manually removed. The high-quality audio can be processed to reflect recording conditions found in forensic casework.

The database can be accessed at: http://databases.forensic-voice-comparison.net/

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5-2-20Audio and Electroglottographic speech recordings

 

Audio and Electroglottographic speech recordings from several languages

We are happy to announce the public availability of speech recordings made as part of the UCLA project 'Production and Perception of Linguistic Voice Quality'.

http://www.phonetics.ucla.edu/voiceproject/voice.html

Audio and EGG recordings are available for Bo, Gujarati, Hmong, Mandarin, Black Miao, Southern Yi, Santiago Matatlan/ San Juan Guelavia Zapotec; audio recordings (no EGG) are available for English and Mandarin. Recordings of Jalapa Mazatec extracted from the UCLA Phonetic Archive are also posted. All recordings are accompanied by explanatory notes and wordlists, and most are accompanied by Praat textgrids that locate target segments of interest to our project.

Analysis software developed as part of the project – VoiceSauce for audio analysis and EggWorks for EGG analysis – and all project publications are also available from this site. All preliminary analyses of the recordings using these tools (i.e. acoustic and EGG parameter values extracted from the recordings) are posted on the site in large data spreadsheets.

All of these materials are made freely available under a Creative Commons Attribution-NonCommercial-ShareAlike-3.0 Unported License.

This project was funded by NSF grant BCS-0720304 to Pat Keating, Abeer Alwan and Jody Kreiman of UCLA, and Christina Esposito of Macalester College.

Pat Keating (UCLA)

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5-2-21Press release: Opening of the ELRA License Wizard

Press Release - Immediate - Paris, France, April 2, 2015

Opening of the ELRA License Wizard

ELRA announces the opening of the License Wizard @ http://wizard.elda.org.

ELRA  is deploying a License Wizard to:

  • support the right-holders in finding the appropriate licenses under which to share/distribute their Language Resources, and
  • clarify the legal obligations applicable in various licensing situations.

Currently, the License Wizard allows the user to choose among several licenses that exist for the use of Language Resources: ELRA, Creative Commons and META-SHARE.
More will be added.

The License Wizard works as a web configurator that helps Right Holders/Users:

- to select a number of legal features and obtain the user license adapted to their selection.
- to define which user licenses they would like to select in order to distribute their Language Resources.
- to integrate the user license terms into a Distribution Agreement that could be proposed to ELRA or META-SHARE  for further distribution through the ELRA Catalogue of Language Resources (http://catalogue.elra.infowww.meta-share.eu).

Background
From the very beginning, ELRA has come across all types of legal issues that arise when exchanging and sharing Language Resources. The association has devoted huge efforts to streamline the licensing processes while continuously monitoring the impacts of regulation changes on the HLT community activities. The first major step was to come up with a few licenses for both the research and the industrial sectors to use the resources available within the ELRA catalogue. Recently, its strong involvement in the META-SHARE infrastructure led to designing and drafting a small set of licenses, inspired by the ELRA licenses but also accounting for the new trends of permissive licenses and free resources, represented in particular by the Creative Commons.

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5-2-22EEG-face tracking- audio 24 GB data set Kara One, Toronto, Canada

We are making 24 GB of a new dataset, called Kara One, freely available. This database combines 3 modalities (EEG, face tracking, and audio) during imagined and articulated speech using phonologically-relevant phonemic and single-word prompts. It is the result of a collaboration between the Toronto Rehabilitation Institute (in the University Health Network) and the Department of Computer Science at the University of Toronto.

 

In the associated paper (abstract below), we show how to accurately classify imagined phonological categories solely from EEG data. Specifically, we obtain up to 90% accuracy in classifying imagined consonants from imagined vowels and up to 95% accuracy in classifying stimulus from active imagination states using advanced deep-belief networks.

 

Data from 14 participants are available here: http://www.cs.toronto.edu/~complingweb/data/karaOne/karaOne.html.

 

If you have any questions, please contact Frank Rudzicz at frank@cs.toronto.edu.

 

Best regards,

Frank

 

 

PAPER Shunan Zhao and Frank Rudzicz (2015) Classifying phonological categories in imagined and articulated speech. In Proceedings of ICASSP 2015, Brisbane Australia

ABSTRACT This paper presents a new dataset combining 3 modalities (EEG, facial, and audio) during imagined and vocalized phonemic and single-word prompts. We pre-process the EEG data, compute features for all 3 modalities, and perform binary classi?cation of phonological categories using a combination of these modalities. For example, a deep-belief network obtains accuracies over 90% on identifying consonants, which is signi?cantly more accurate than two baseline supportvectormachines. Wealsoclassifybetweenthedifferent states (resting, stimuli, active thinking) of the recording, achievingaccuraciesof95%. Thesedatamaybeusedtolearn multimodal relationships, and to develop silent-speech and brain-computer interfaces.

 

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5-2-23TORGO data base free for academic use.

In the spirit of the season, I would like to announce the immediate availability of the TORGO database free, in perpetuity for academic use. This database combines acoustics and electromagnetic articulography from 8 individuals with speech disorders and 7 without, and totals over 18 GB. These data can be used for multimodal models (e.g., for acoustic-articulatory inversion), models of pathology, and augmented speech recognition, for example. More information (and the database itself) can be found here: http://www.cs.toronto.edu/~complingweb/data/TORGO/torgo.html.

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5-2-24Datatang

Datatang is a global leading data provider that specialized in data customized solution, focusing in variety speech, image, and text data collection, annotation, crowdsourcing services.

 

1, Speech data collection

2, Speech data synthesis

3, Speech data transcription

I’ve attached our company introduction as reference, as well as available speech data lists as follows:

US English Speech Data

300 people, about 200 hours

Uyghur Speech Data

2,500 people, about 1,000 hours

German Speech Data

100 people, about 40 hours

French Speech Data

100 people, about 40 hours

Spanish Speech Data

100 people, about 40 hours

Korean Speech Data

100 people, about 40 hours

Italian Speech Data

100 people, about 40 hours

Thai Speech Data

100 people, about 40 hours

Portuguese Speech Data

300 People, about 100 hours

Chinese Mandarin Speech Data

4,000 people, about 1,200 hours

Chinese Speaking English Speech Data

3,700 people, 720 hours

Cantonese Speech Data

5,000 people, about 1,400 hours

Japanese Speech Data

800 people, about 270 hours

Chinese Mandarin In-car Speech Data

690 people, about 245 hours

Shanghai Dialect Speech Data

2,500 people, about 1,000 hours

Southern Fujian Dialect Speech Data

2,500 people, about 1,000 hours

Sichuan Dialect Speech Data

2,500 people, about 860 hours

Henan Dialect Speech Data

400 people, about 150 hours

Northeastern Dialect Speech Data

300 people, 80 hours

Suzhou Dialect Speech Data

270 people, about 110 hours

Hangzhou Dialect Speech Data

400 people, about 170 hours

Non-Native Speaking Chinese Speech Data

1,100 people, about 73 hours

Real-world Call Center Chinese Speech Data

650 hours, more than 5,000 people

Mobile-end Real-world Voice Assistant Chinese Speech Data

4,000 hours, more than 2,000,000 people

Heavy Accent Chinese Speech Data

2,000 people, more than 1,000 hours

 

If you find any particular interested datasets, we could provide you samples with costs too.

 

Regards

 

Runze Zhao

zhaorunze@datatang.com 

Oversea Sales Manager | Datatang Technology 

China

M: +86 185 1698 2583

18 Zhongguancun St.

Kemao Building Tower B 18F

Beijing 100190

 

US

M: +1 617 763 4722 

640 W California Ave, Suite 210

Sunnyvale, CA 94086


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5-2-25The International Standard Language Resource Number (ISLRN) assigned to LRE Map 2016 Language Resources

Press Release ? Immediate

 

 

Paris, France, June 8, 2017

 

 

The International Standard Language Resource Number (ISLRN) assigned to LRE Map 2016 Language Resources

 

 

As a follow-up of the LRE Map 2016 initiative, ELRA has processed the information on existing and newly-created Language Resources provided by the authors submitting at LREC 2016 Conference (http://lrec2016.lrec-conf.org). In order to increase the visibility of these resources, ELRA has allocated ISLRNs to 106 submitted languages resources. They distribute as follows:

 

 

  • 73 Corpora (ca. written, spoken, multimodal)
  • 30 Lexicons (including ontologies)
  • 3 Evaluation Data

 

 

The meta-information for these language resources is also available on the ISLRN website with a broad international audience.

 

 

Background

 

 

As part of an international effort to document and archive the various language resource development efforts around the world, a system of assigning ISLRNs was established in November 2013. The ISLRN is a unique persistent identifier to be assigned to each language resource. The establishment of ISLRNs was a major step in the networked and shared world of human language technologies. Unique resources must be identified as they are, and meta-catalogues require a common identification format to manage data correctly. Therefore, language resources should carry identical identification schemes independent of their representations, whatever their types and wherever their physical locations (on hard drives, internet or intranet). Visit: http://islrn.org/.

 

 

About LRE Map

 

 

Initiated by ELRA and FlareNet at LREC 2010 (http://www.lrec-conf.org), the LRE Map is a mechanism intended to monitor the use and creation of language resources by collecting information on both existing and newly-created resources during the submission process. Apart from providing a portrait of the resources behind the community, of their uses and usability, the LRE Map intends to be a measuring instrument for monitoring the field of language resources. The feature has been so successful that it has been implemented also at other major conferences like COLING, IJCNLP, Interspeech, LTC, ACLHT, O-COCOSDA, RANLP, in addition to the LRE Journal. Visit: http://lremap.elra.info

 

 

About ELRA

 

 

The European Language Resources Association (ELRA) is a non-profit-making organisation founded by the European Commission in 1995, with the mission of providing a clearing house for language resources and promoting human language technologies.

 

 

To find out more about ELRA, please visit the website: http://www.elra.info

 

Contact: info@elda.org


 

The International Standard Language Resource Number (ISLRN) is becoming an increasingly widespread persistent identifier

 

Since the deployment of ISLRN, 3 years ago, the number of Language Resources which were allocated an ISLRN has grown significantly to reach 2500+. These LRs include raw and annotated corpora, lexicons and dictionaries, speech resources (conversational, synthesis, etc.), evaluation sets and multimodal resources, and cover 219 distinct languages (including sign languages).

 

In the first place, the ISLRN system has been endorsed by two large data centers, namely ELRA (European Language Resources Association) and LDC (Linguistic Data Consortium) which team up to maintain jointly the assignment process. Other significant contributions come from institutions like the Joint Research Centre (JRC), the Resource Management Agency (RMA), the Institute for Applied Linguistics (IULA) at the Universitat Pompeu Fabra (UPF).

 

Moreover, authors are invited to quote the ISLRN of each Language Resource they are referring to in the paper(s) they are submitting to LREC Conferences, which makes the persistent identifier a key factor of the LR citation process.

 

 

 

Background

 

As part of an international effort to document and archive the various Language Resource development efforts around the world, a system assigning ISLRNs was established in November 2013 and deployed in April 2014. The ISLRN is a unique persistent identifier to be assigned to each Language Resource. The establishment of ISLRNs was a major step in the networked and shared world of Human Language Technologies. Unique resources must be identified as they are, and meta-catalogues require a common identification format to manage data correctly. Therefore, Language Resources should carry identical identification schemes regardless their representations, their types and their storage place (hard drives, internet or intranet) (http://islrn.org/).

 

About ELRA

 

The European Language Resources Association (ELRA) is a non-profit-making organisation founded by the European Commission in 1995, with the mission of providing a clearing house for Language Resources and promoting Human Language Technologies.

 

To find out more about ELRA, please visit the website: http://www.elra.info

 

References

 

LDC: https://www.ldc.upenn.edu

 

JRC: https://ec.europa.eu/jrc/en/research-topic/internet-surveillance-systems

 

RMA: http://rma.nwu.ac.za

 

UPF: http://www.iula.upf.edu  and https://www.upf.edu/web/universitat

 

LREC Conferences: www.lrec-conf.org

 

 

 

Read also: Valérie Mapelli, Vladimir Popescu, Lin Liu and Khalid Choukri, Language Resource Citation: the ISLRN Dissemination and Further Developments, in Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016), Portoro?, Slovenia: http://www.lrec-conf.org/proceedings/lrec2016/summaries/1251.html

 

 

 

Contact: mapelli@elda.org



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5-3 Software
5-3-1ROCme!: a free tool for audio corpora recording and management

ROCme!: nouveau logiciel gratuit pour l'enregistrement et la gestion de corpus audio.

Le logiciel ROCme! permet une gestion rationalisée, autonome et dématérialisée de l’enregistrement de corpus lus.

Caractéristiques clés :
- gratuit
- compatible Windows et Mac
- interface paramétrable pour le recueil de métadonnées sur les locuteurs
- le locuteur fait défiler les phrases à l'écran et les enregistre de façon autonome
- format audio paramétrable

Téléchargeable à cette adresse :
www.ddl.ish-lyon.cnrs.fr/rocme

 
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5-3-2VocalTractLab 2.0 : A tool for articulatory speech synthesis

VocalTractLab 2.0 : A tool for articulatory speech synthesis

It is my pleasure to announce the release of the new major version 2.0 of VocalTractLab. VocalTractLab is an articulatory speech synthesizer and a tool to visualize and explore the mechanism of speech production with regard to articulation, acoustics, and control. It is available from http://www.vocaltractlab.de/index.php?page=vocaltractlab-download .
Compared to version 1.0, the new version brings many improvements in terms of the implemented models of the vocal tract, the vocal folds, the acoustic simulation, and articulatory control, as well as in terms of the user interface. Most importantly, the new version comes together with a manual.

If you like, give it a try. Reports on bugs and any other feedback are welcome.

Peter Birkholz

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5-3-3Bob signal-processing and machine learning toolbox (v.1.2..0)


    The release 1.2.0 of the Bob signal-processing and machine learning toolbox is available .
    Bob provides both efficient implementations of several machine     learning algorithms as well as a framework to help researchers to     publish reproducible research.
   
   

It is developed by the Biometrics Group at Idiap in  Switzerland.

   
    The previous release of Bob was providing:
    * image, video and audio IO interfaces such as jpg, avi, wav, 
    * database accessors such as FRGC, Labelled Face in the Wild, and many     others,
    *mage processing: Local Binary Patterns (LBPs), Gabor Jets,  SIFT,
    * machines  and trainers such as Support Vector Machines (SVMs), k-Means,     Gaussian Mixture Models (GMMs), Inter-Session Variability modeling     (ISV), Joint Factor Analysis (JFA), Probabilistic Linear     Discriminant Analysis (PLDA), Bayesian intra/extra (personal)     classifier,
   
    The new release of Bob has brought the following features and/or improvements, such as:
    * Unified implementation of Local Binary Patterns (LBPs),
    * Histograms of Oriented Gradients (HOG) implementation,
    * Total variability (i-vector) implementation,
    * Conjugate gradient based-implementation for logistic regression,
    * Improved multi-layer perceptrons implementation (Back-propagation can now be easily used in combination with any optimizer -- i.e     L-BFGS),
    * Pseudo-inverse-based method for Linear Discriminant Analysis,
    * Covariance-based method for Principal Component Analysis,
    * Whitening and within-class covariance normalization techniques,
    * Module for object detection and keypoint localization     (bob.visioner),
    * Module for audio processing including feature extraction such as LFCC and     MFCC,
    * Improved extensions (satellite packages), that now support both     Python and C++ code, within an easy to use framework,
    * Improved documentation and add new tutorials,
    * Support for Intel's MKL (in addition to ATLAS),
    * Extend supported platforms (Arch Linux).
   
    This release represents a major milestone in Bob with plenty of  functionality improvements (>640 commits in total) and plenty of bug fixes.
    • Sources and Documentation
    • Binary packages:
    •     Ubuntu: 10.04, 12.04, 12.10 and 13.04
    • For     Mac OSX: works with 10.6 (Snow Leopard), 10.7 (Lion) and 10.8     (Mountain Lion)
   
    For instructions on how to install pre-packaged version on Ubuntu or     OSX, consult our quick       installation instructions  (N.B. OS X macport has not yet been     upgraded. This will be done very soon. cf. https://trac.macports.org/ticket/39831 ).
   
   
    Best regards,
    Elie Khoury (on Behalf of the Biometric Group at Idiap lead by Sebastien Marcel)
   
     
     ---    

 Dr. Elie Khoury Post Doctorant Biometric Person Recognition Group 
IDIAP Research Institute (Switzerland) Tel : +41 27 721 77 23
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5-3-4COVAREP: A Cooperative Voice Analysis Repository for Speech Technologies
======================
CALL for contributions
======================
 
We are pleased to announce the creation of an open-source repository of advanced speech processing algorithms called COVAREP (A Cooperative Voice Analysis Repository for Speech Technologies). COVAREP has been created as a GitHub project (https://github.com/covarep/covarep) where researchers in speech processing can store original implementations of published algorithms.
 
Over the past few decades a vast array of advanced speech processing algorithms have been developed, often offering significant improvements over the existing state-of-the-art. Such algorithms can have a reasonably high degree of complexity and, hence, can be difficult to accurately re-implement based on article descriptions. Another issue is the so-called 'bug magnet effect' with re-implementations frequently having significant differences from the original. The consequence of all this has been that many promising developments have been under-exploited or discarded, with researchers tending to stick to conventional analysis methods.
 
By developing the COVAREP repository we are hoping to address this by encouraging authors to include original implementations of their algorithms, thus resulting in a single de facto version for the speech community to refer to.
 
We envisage a range of benefits to the repository:
1) Reproducible research: COVAREP will allow fairer comparison of algorithms in published articles.
2) Encouraged usage: the free availability of these algorithms will encourage researchers from a wide range of speech-related disciplines (both in academia and industry) to exploit them for their own applications.
3) Feedback: as a GitHub project users will be able to offer comments on algorithms, report bugs, suggest improvements etc.
 
SCOPE
We welcome contributions from a wide range of speech processing areas, including (but not limited to): Speech analysis, synthesis, conversion, transformation, enhancement, speech quality, glottal source/voice quality analysis, etc.
 
REQUIREMENTS
In order to achieve a reasonable standard of consistency and homogeneity across algorithms we have compiled a list of requirements for prospective contributors to the repository. However, we intend the list of the requirements not to be so strict as to discourage contributions.
  • Only published work can be added to the   repository
  • The code must be available as open source
  • Algorithms should be coded in Matlab, however we   strongly encourage authors to make the code compatible with Octave in order to   maximize usability
  • Contributions have to comply with a Coding   Convention (see GitHub site for coding convention and template). However, only   for normalizing the inputs/outputs and the documentation. There is no   restriction for the content of the functions (though, comments are obviously   encouraged).
 
LICENCE
Getting contributing institutions to agree to a homogenous IP policy would be close to impossible. As a result COVAREP is a repository and not a toolbox, and each algorithm will have its own licence associated with it. Though flexible to different licence types, contributions will need to have a licence which is compatible with the repository, i.e. {GPL, LGPL, X11, Apache, MIT} or similar. We would encourage contributors to try to obtain LGPL licences from their institutions in order to be more industry friendly.
 
CONTRIBUTE!
We believe that the COVAREP repository has a great potential benefit to the speech research community and we hope that you will consider contributing your published algorithms to it. If you have any questions, comments issues etc regarding COVAREP please contact us on one of the email addresses below. Please forward this email to others who may be interested.
 
Existing contributions include: algorithms for spectral envelope modelling, adaptive sinusoidal modelling, fundamental frequncy/voicing decision/glottal closure instant detection algorithms, methods for detecting non-modal phonation types etc.
 
Gilles Degottex <degottex@csd.uoc.gr>, John Kane <kanejo@tcd.ie>, Thomas Drugman <thomas.drugman@umons.ac.be>, Tuomo Raitio <tuomo.raitio@aalto.fi>, Stefan Scherer <scherer@ict.usc.edu>
 
 
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5-3-5Release of the version 2 of FASST (Flexible Audio Source Separation Toolbox).
Release of the version 2 of FASST (Flexible Audio Source Separation Toolbox). http://bass-db.gforge.inria.fr/fasst/ This toolbox is intended to speed up the conception and to automate the implementation of new model-based audio source separation algorithms. It has the following additions compared to version 1: * Core in C++ * User scripts in MATLAB or python * Speedup * Multichannel audio input We provide 2 examples: 1. two-channel instantaneous NMF 2. real-world speech enhancement (2nd CHiME Challenge, Track 1)
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5-3-6Cantor Digitalis, an open-source real-time singing synthesizer controlled by hand gestures.

We are glad to announce the public realease of the Cantor Digitalis, an open-source real-time singing synthesizer controlled by hand gestures.


It can be used e.g. for making music or for singing voice pedagogy.

A wide variety of voices are available, from the classic vocal quartet (soprano, alto, tenor, bass), to the extreme colors of childish, breathy, roaring, etc. voices.  All the features of vocal sounds are entirely under control, as the synthesis method is based on a mathematic model of voice production, without prerecording segments.

The instrument is controlled using chironomy, i.e. hand gestures, with the help of interfaces like stylus or fingers on a graphic tablet, or computer mouse. Vocal dimensions such as the melody, vocal effort, vowel, voice tension, vocal tract size, breathiness etc. can easily and continuously be controlled during performance, and special voices can be prepared in advance or using presets.

Check out the capabilities of Cantor Digitalis, through performances extracts from the ensemble Chorus Digitalis:
http://youtu.be/_LTjM3Lihis?t=13s.

In pratice, this release provides:
  • the synthesizer application
  • the source code in the form of a Max package (GPL-like license)
  • a documentation for the musician and another for the developper
What do you need ?
  • a Mac OSX
  • ideally a Wacom graphic tablet, but it also works with your computer mouse
  • for the developers, the Max software
Interested ?
  • To download the Cantor Digitalis, click here
  • To subscribe to the Cantor Digitalisnewsletter and/or the forum list, or to contact the developers, click here
  • To learn about the Chorus Digitalis, ensemble of Cantor Digitalisand watch videos of performances, click here
  • For more details about the Cantor Digitalis, click here
 
Regards,
 
The Cantor Digitalis team (who loves feedback — cantordigitalis@limsi.fr)
Christophe d'Alessandro, Lionel Feugère, Olivier Perrotin
http://cantordigitalis.limsi.fr/
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5-3-7MultiVec: a Multilingual and MultiLevel Representation Learning Toolkit for NLP

 

We are happy to announce the release of our new toolkit “MultiVec” for computing continuous representations for text at different granularity levels (word-level or sequences of words). MultiVec includes Mikolov et al. [2013b]’s word2vec features, Le and Mikolov [2014]’s paragraph vector (batch and online) and Luong et al. [2015]’s model for bilingual distributed representations. MultiVec also includes different distance measures between words and sequences of words. The toolkit is written in C++ and is aimed at being fast (in the same order of magnitude as word2vec), easy to use, and easy to extend. It has been evaluated on several NLP tasks: the analogical reasoning task, sentiment analysis, and crosslingual document classification. The toolkit also includes C++ and Python libraries, that you can use to query bilingual and monolingual models.

 

The project is fully open to future contributions. The code is provided on the project webpage (https://github.com/eske/multivec) with installation instructions and command-line usage examples.

 

When you use this toolkit, please cite:

 

@InProceedings{MultiVecLREC2016,

Title                    = {{MultiVec: a Multilingual and MultiLevel Representation Learning Toolkit for NLP}},

Author                   = {Alexandre Bérard and Christophe Servan and Olivier Pietquin and Laurent Besacier},

Booktitle                = {The 10th edition of the Language Resources and Evaluation Conference (LREC 2016)},

Year                     = {2016},

Month                    = {May}

}

 

The paper is available here: https://github.com/eske/multivec/raw/master/docs/Berard_and_al-MultiVec_a_Multilingual_and_Multilevel_Representation_Learning_Toolkit_for_NLP-LREC2016.pdf

 

Best regards,

 

Alexandre Bérard, Christophe Servan, Olivier Pietquin and Laurent Besacier

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5-3-8An android application for speech data collection LIG_AIKUMA
We are pleased to announce the release of LIG_AIKUMA, an android application for speech data collection, specially dedicated to language documentation. LIG_AIKUMA is an improved version of the Android application (AIKUMA) initially developed by Steven Bird and colleagues. Features were added to the app in order to facilitate the collection of parallel speech data in line with the requirements of a French-German project (ANR/DFG BULB - Breaking the Unwritten Language Barrier). 
 
The resulting app, called LIG-AIKUMA, runs on various mobile phones and tablets and proposes a range of different speech collection modes (recording, respeaking, translation and elicitation). It was used for field data collections in Congo-Brazzaville resulting in a total of over 80 hours of speech.
 
Users who just want to use the app without access to the code can download it directly from the forge direct link: https://forge.imag.fr/frs/download.php/706/MainActivity.apk 
Code is also available on demand (contact elodie.gauthier@imag.fr and laurent.besacier@imag.fr).
 
More details on LIG_AIKUMA can be found on the following paper: http://www.sciencedirect.com/science/article/pii/S1877050916300448
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5-3-9(2017-09-20) 11th Oxford Dysfluency Conference , Oxford, UK

11th Oxford Dysfluency Conference 
Challenge and Change

20-23 September 2017 | St Catherine’s College, Oxford, UK

The 11th Oxford Dysfluency Conference (ODC), under the theme ‘Challenge and Change’, is to be held at St Catherine’s College Oxford from 20-23 September, 2017. ODC has a reputation as one of the leading international scientific conferences in the field of dysfluency.

Abstract submission deadline: 31 March 2017.


The conference brings together researchers and clinicians, providing a showcase and forum for discussion and collegial debate about the most current and innovative research and clinical practices. Throughout the history of ODC, the primary aim has been to bridge the gap between research and clinical practice.

The conference seeks to promote research that informs management, with interventions that are supported by sound theory and which inform future research.

In 2017, the goal is to encourage discussion and debate that will challenge and enhance our perspectives and understanding of research; the nature of stuttering and / or cluttering; and management across the ages.

Topics

Abstract submission deadline: 31 March 2017

Abstracts are now invited on the following topics. They should be submitted using the online abstract submission system.

  1. New perspectives on assessment and therapy in children
  2. New perspectives on assessment and therapy in adolescents
  3. New perspectives on assessment and therapy in adults
  4. Issues, variables, and controversies in assessment and outcome
  5. Supporting the next generation of clinicians and researchers
  6. Evidence in practice
  7. Neurological foundations

The 2017 conference will enable delegates to:

  • Present and learn from the latest research developments and findings
  • Explore issues relating to the nature of stuttering and / or cluttering and its treatment
  • Develop knowledge and clinical skills for working with children and adults who stutter and / or clutter
  • Advance research in the field of dysfluency
  • Consider ways to integrate research into clinical practice
  • Support and encourage new researchers in the field
  • Develop collaborations with researchers working in dysfluency
  • Provide informal opportunities to meet and discuss ideas with leading experts in the field in a friendly environment
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5-3-10Web services via ALL GO from IRISA-CNRS

It is our pleasure to introduce A||GO (https://allgo.inria.fr/ or http://allgo.irisa.fr/), a platform providing a collection of web-services for the automatic analysis of various data, including multimedia content across modalities. The platform builds on the back-end web service deployment infrastructure developed and maintained by  Inria?s  Service for Experimentation and Development (SED). Originally dedicated to multimedia content, A||GO progressively broadened to other fields such as computational biology, networks and telecommunications, computational graphics or computational physics.

As part of the CNRS PlaSciDo initiative [1], the Linkmedia team at IRISA / Inria Rennes is making available via A||GO a number of web services devoted to multimedia content analysis across modalities (language, audio, image, video). The web services provided currently include research results from the Linkmedia team as well as contribution from a number of partners. A list of the services available by the date is given below and the current state is available at
https://www-linkmedia.irisa.fr/software along with demo videos. Most web services are interoperable, facilitating the implementation of a multimedia content analysis processing chain, and are free to use for trial, prototyping or lab work. A brief and free account creation step will allow you to execute the web-services using either the graphical interface or a command line via a dedicated API.

We expect the number of web services to grow over time and invite interested parties to contact us should they wish to contribute the multimedia web service offer of A||GO.

List of multimedia content analysis tools currently available on A||GO:
- Audio Processing
        SaMuSa: music/speech segmentation
        SilAD: silence detection
        Radi.sh: repeated audio motif discovery
        LORIA STS v2: speech transcription for the French language from LORIA
        Multi channel BSS locate: audio source localization toolbox from IRISA-PANAMA
        A-spade: audio declipper from IRISA-PANAMA
        Transvox: voice faker from LORIA
- Natural Language Processing
        NERO: name entity recognition
        TermEx: keywords/indexing terms detection
        Otis!: topic segmentation
        Hi-tost: hierarchical topic structuring
- Video Processing
        Vidseg: video shot segmentation
        HUFA: face detection and tracking
Shortcuts to Linkmedia services are also available here:
https://www-linkmedia.irisa.fr/software/
 
For more information don't hesitate to contact us (
contact-multimedia-allgo@irisa.fr
). 

 
Gabriel Sargent and Guillaume Gravier
--
Linkmedia
IRISA - CNRS
Rennes, France

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5-3-11Clickable map - Illustrations of the IPA

Clickable map - Illustrations of the IPA


We have produced a clickable map showing the Illustrations of the International Phonetic
Alphabet.

The map is being updated with each new issue of the Journal of the International Phonetic
Association.

https://richardbeare.github.io/marijatabain/ipa_illustrations_all.html

Marija Tabain - La Trobe University, Australia
Richard Beare - Monash University & MCRI, Australia

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5-3-12LIG-Aikuma running on mobile phones and tablets

 


Dear all,

LIG is pleased to inform you that the website for the app Lig-Aikuma is online: https://lig-aikuma.imag.fr/
In the same time, an update of Lig-Aikuma (V3) was made available (see website).      

LIG-AIKUMA is a free Android app running on various mobile phones and tablets. The app proposes a range of different speech collection modes (recording, respeaking, translation and elicitation) and offers the possibility to share recordings between users. LIG-AIKUMA is built upon the initial AIKUMA app developed by S. Bird & F. Hanke (see https://en.wikipedia.org/wiki/Aikuma  for more information)

Improvements of the app:

  • Visual upgrade:
    + Waveform visualizer on the Respeaking and Translation modes (possibility to zoom in/out the audio signal)
    + File explorer included in all modes, to facilitate the navigation between files
    + New Share mode to share recordings between devices (by Bluetooth, Mail, NFC if available)
    + French and German languages available. In addition to English, the application now supports French and German languages. Lig-Aikuma uses by default the language of the phone/tablet.
    + New icons, more consistent to discriminate all type of files (audio, text, image, video)
  • Conceptual upgrade:
    + New name for the root project: ligaikuma ?> /! Henceforth, all data will be stored into this directory instead of ?aikuma? (in the previous versions of the app). This change doesn?t have compatibility issues. In the file explorer of the mode, the default position is this root directory. Just go back once with the left grey arrow (on the lower left of the screen) and select the ?aikuma? directory to access to your old recordings
    + Generation of a PDF consent form (from informations filled in the metadata form) that can be signed by linguist and speaker thanks to a pdf annotation tool (like Adobe Fill & Sign mobile app)
    + Generation of a CSV file which can be imported in Elan software: it will automatically create segmented tier, as it was done during a respeaking or a translation session. It will also mention by a ?non-speech? label that a segment has no speech.
    + Géolocalisation of the recordings
    + Respeak an elicit file: it is now possible to use in Respeaking or Translation mode an audio file initially recorded in Elicitation mode
  • Structural upgrade:
    + Undo button on Elicitation to erase/redo the current recording
    + Improvement session backup on Elicitation
    + Non-speech button in Respeaking and Translation modes to indicate by a comment that the segment does not contain speech (but noise or silent for instance)
    + Automatic speaker profile creation to quickly fill in the metadata infos if several sessions with a same speaker
Best regards,

Elodie Gauthier & Laurent Besacier
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