Techniques for Noise Robustness in Automatic Speech Recognition
Tuomas Virtanen, Rita Singh, Bhiksha Raj (editors)
ISBN: 978-1-1199-7088-0
Publisher: Wiley

Automatic speech recognition (ASR) systems are finding increasing use in everyday life. Many of the commonplace environments where the systems are used are noisy, for example users calling up a voice search system from a busy cafeteria or a street. This can result in degraded speech recordings and adversely affect the performance of speech recognition systems. As the use of ASR systems increases, knowledge of the state-of-the-art in techniques to deal with such problems becomes critical to system and application engineers and researchers who work with or on ASR technologies. This book presents a comprehensive survey of the state-of-the-art in techniques used to improve the robustness of speech recognition systems to these degrading external influences.

Key features:

*Reviews all the main noise robust ASR approaches, including signal separation, voice activity detection, robust feature extraction, model compensation and adaptation, missing data techniques and recognition of reverberant speech.
*Acts as a timely exposition of the topic in light of more widespread use in the future of ASR technology in challenging environments.
*Addresses robustness issues and signal degradation which are both key requirements for practitioners of ASR.
*Includes contributions from top ASR researchers from leading research units in the field

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Understanding Prosody: The Role of Context, Function and Communication

Ed. by Niebuhr, Oliver

Series:Language, Context and Cognition 13,   De Gruyter

http://www.degruyter.com/view/product/186201?format=G or http://linguistlist.org/pubs/books/get-book.cfm?BookID=63238

The volume represents a state-of-the-art snapshot of the research on prosody for phoneticians, linguists and speech technologists. It covers well-known models and languages. How are prosodies linked to speech sounds? What are the relations between prosody and grammar? What does speech perception tell us about prosody, particularly about the constituting elements of intonation and rhythm? The papers of the volume address questions like these with a special focus on how the notion of context-based coding, the knowledge of prosodic functions and the communicative embedding of prosodic elements can advance our understanding of prosody.

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 Albert Di Cristo: « La Prosodie de la Parole : Une Introduction », Editions de Boeck-Solal (296 p). 

Sommaire : 

Avant –propos, Introduction, ;

 Ch.1 : Eléments de définition ; 

 Ch 2. Situation de la prosodie dans le champ des sciences du langage et dans l’étude de la communication ; 

Ch 3. La prosodie sur les deux versants de la communication orale interindividuelle (production et compréhension) ; 

Ch 4. La prosodie et le cerveau ;

 Ch 5. La matérialité de la prosodie ; 

Ch 6. Les niveau d’analyse et de représentation de la prosodie ; 

Ch 7. Les théories, les modèles de la prosodie et leurs appareils formels ;

 Ch 8 La fonctionnalité plurielle de la prosodie ; 

Ch 9. Les relations de la prosodie avec les sens ; 

Epilogue. 

Suggestions de lecture ;

 Index des termes ; 

Index des noms propres.

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Björn Schuller, Anton Batliner Computational Paralinguistics: Emotion, Affect and Personality in Speech and Language Processing Wiley, ISBN: 978-1-119-97136-8, 344 pages, November 2013 Description - This book presents the methods, tools and techniques that are currently being used to recognise (automatically) the affect, emotion, personality and everything else beyond linguistics (‘paralinguistics’) expressed by or embedded in human speech and language. - It is the first book to provide such a systematic survey of paralinguistics in speech and language processing. The technology described has evolved mainly from automatic speech and speaker recognition and processing, but also takes into account recent developments within speech signal processing, machine intelligence and data mining. - Moreover, the book offers a hands-on approach by integrating actual data sets, software, and open-source utilities which will make the book invaluable as a teaching tool and similarly useful for those professionals already in the field. Key features: - Provides an integrated presentation of basic research (in phonetics/linguistics and humanities) with state-of-the-art engineering approaches for speech signal processing and machine intelligence. - Explains the history and state of the art of all of the sub-fields which contribute to the topic of computational paralinguistics. - Covers the signal processing and machine learning aspects of the actual computational modelling of emotion and personality and explains the detection process from corpus collection to feature extraction and from model testing to system integration. - Details aspects of real-world system integration including distribution, weakly supervised learning and confidence measures. - Outlines machine learning approaches including static, dynamic and context-sensitive algorithms for classification and regression. - Includes a tutorial on freely available toolkits, such as the open-source ‘openEAR’ toolkit for emotion and affect recognition co-developed by one of the authors, and a listing of standard databases and feature sets used in the field to allow for immediate experimentation enabling the reader to build an emotion detection model on an existing corpus. Links: - The book: http://eu.wiley.com/WileyCDA/WileyTitle/productCd-1119971365.html - Table of Contents (pdf): http://media.wiley.com/product_data/excerpt/65/11199713/1119971365-16.pdf - Chapter01 (pdf): http://media.wiley.com/product_data/excerpt/65/11199713/1119971365-14.pdf 

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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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Tackling the Complexity in Speech

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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 '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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In this newsletter:

Fall 2015 Data Scholarship Program

New publications:

English News Text Treebank: Penn Treebank Revised

TS Wikipedia

The Walking Around Corpus

Fall 2015 Data Scholarship Program

Applications are now being accepted through Tuesday, September 15, 2015 for the Fall 2015 LDC Data Scholarship program. The LDC Data Scholarship program provides university students with access to LDC data at no-cost.

This program is open to students pursuing both undergraduate and graduate studies in an accredited college or university. LDC Data Scholarships are not restricted to any particular field of study; however, students must demonstrate a well-developed research agenda and a bona fide inability to pay. The selection process is highly competitive.

The application consists of two parts:

(1) Data Use Proposal. Applicants must submit a proposal describing their intended use of the data. The proposal should state which data the student plans to use and how the data will benefit their research project as well as information on the proposed methodology or algorithm.

Applicants should consult the LDC Catalog for a complete list of data distributed by LDC. Due to certain restrictions, a handful of LDC corpora are restricted to members of the Consortium. Applicants are advised to select a maximum of one to two databases.

(2) Letter of Support. Applicants must submit one letter of support from their thesis adviser or department chair. The letter must confirm that the department or university lacks the funding to pay the full non-member fee for the data and verify the student's need for data.

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

New publications

(1) English News Text Treebank: Penn Treebank Revised was developed by LDC with funding through a gift from Google Inc. It consists of a combination of automated and manual revisions of the Penn Treebank annotation of Wall Street Journal (WSJ) stories. The data is comprised of 1,203,648 word-level tokens in 49,191 sentence-level tokens -- in all 2,312 of the original Penn Treebank WSJ files.

This release includes revised tokenization, part-of-speech, and syntactic treebank annotation intended to bring the full WSJ treebank section into compliance with the agreed-upon policies and updates implemented for current English treebank annotation specifications at LDC. Examples include English Web Treebank (LDC2012T13), OntoNotes (LDC2013T19), and English translation treebanks such as English Translation Treebank: An-Nahar Newswire (LDC2012T02). English Treebank Supplemental Guidelines are included in this release.

English News Text Treebank: Penn Treebank Revised is distributed via web download.

2015 Subscription Members will automatically receive two copies of this corpus on disc.  2015 Standard Members may request a copy as part of their 16 free membership corpora.  Non-members may license this data for US$175.

 *

(2) TS Wikipedia is a collection of approximately 1.6 million processed Turkish Wikipedia pages. The data is tokenized and includes part-of-speech tags, morphological analysis, lemmas, bi-grams and tri-grams.

The data is in a word-per-line format with five tab-separated columns: token, part-of-speech tag, morphological analysis, lemma and corrected token spelling if needed. All data is presented in UTF-8 XML files and was selected and filtered to reduce non-Turkish characters, mathematical formulas and non-Turkish entries.

TS Wikipedia is distributed via web download.

2015 Subscription Members will automatically receive two copies of this corpus on disc.  2015 Standard Members may request a copy as part of their 16 free membership corpora.  Non-members may license this data for US$100.  TS Wikipedia is made available to for-profit members under the LDC For-Profit Membership Agreement and to not-for-profit members and non-members under the Creative Commons Attribution-Noncommercial Share Alike 3.0 license.

 *

(3) The Walking Around Corpus was developed by Stony Brook University and is comprised of approximately 33 hours of navigational telephone dialogues from 72 speakers (36 speaker pairs). Participants were Stony Brook University students who identified themselves as native English speakers.

This corpus was elicited using a navigation task in which one person directed another to walk to 18 unique destinations on Stony Brook University’s West campus. The direction-giver remained inside the lab and gave directions on a landline telephone to the pedestrian who used a mobile phone. As they visited each location, the pedestrians took a picture of each of the 18 destinations using the mobile phone. Pairs conversed spontaneously as they completed the task. The pedestrians' locations were tracked using their cell phones' GPS systems. The pedestrians did not have any maps or pictures of the target destinations and therefore relied on the direction-giver's verbal directions and descriptions to locate and photograph the target destinations.

Each digital audio file was transcribed with time stamps. The corpus material also includes the visual materials (pictures and maps) used to elicit the dialogues, data about the speakers' relationship, spatial abilities and memory performance, and other information.

All audio is presented as 8000Hz, 16-bit flac compressed wav. Transcripts are presented as xls spreadsheets.

The Walking Around Corpus is distributed via web download.

2015 Subscription Members will automatically receive two copies of this corpus on disc.  2015 Standard Members may request a copy as part of their 16 free membership corpora.  Non-members may license this data for US$1000.

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Appen ButlerHill 

A global leader in linguistic technology solutions

RECENT CATALOG ADDITIONS—MARCH 2012

1. Speech Databases

1.1 Telephony

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

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.

                                                         www.appenbutlerhill.com

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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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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 1^er 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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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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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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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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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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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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Speechocean – update (August 2015):

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. Mexican Spanish Speech Recognition Database (Mobile)-300 Speakers

ID: King-ASR-143

This is a 3-channel Mexican Spanish mobile speech database, which is collected over three mobile phone simultaneously (android mobiles, iPhone and windows phones) in Mexico. This database was performed in a quiet environment.
The prompts were the phonetically rich sentences. Due to the potential cognitive load of saying these sentences by the subjects, we took care to choose natural sentences of length between 5 and 25 words. The raw sentences are selected from different domain: Conversations, News, etc. We did remove a number of sentences that includes offensive or negative words or phrase. In order to achieve a good phone balance, we choose sentences from the sentences list to fill out our number. Finally, we had around 29995 unique sentences in our list of sentences, with each of them repeated less than 4 times among different speakers.
The corpus contains the recordings of 270,711 utterances which were from 303 speakers. The recording time is about 477 hours (3-channel), including the leading silence (about 500 ms) and the trailing silence (about 500 ms). The total size of this database is about 51 GB.

2. Argentinean Spanish Speech Recognition Database(Desktop)-200 Speakers

ID: King-ASR-281

This is a 4-channel Spanish desktop speech database, which is collected over 4 different microphones simultaneously. The project was performed in Argentina; cover all the cities, for example: BuenosAires, Cordoba, Lanus, Cordoba...

Each Speaker was recorded around 300 sentences which were selected from a pool of phonetically rich sentences in approximate 80 minutes as natural as possible. The recording was performed in a quiet office environment.

This database is performed in quiet office environment. The corpus contains the recordings of 236,232 utterances of Spanish speech data which were from 200 speakers. The pure recording time is about 358 hours (4-channel), including the leading silence (about 500 ms) and the trailing silence (about 500 ms). The total size of this database is 141 GB.

A pronunciation lexicon with a phonemic transcription in SAMPA was carefully made by covering all the words in the transcription files.

3. Chilean Spanish Speech Recognition Database -(Mobile)-300 Speakers

ID: King-ASR-290

This is a 3-channel Chilean Spanish speech database, which is collected over 3 different mobile operating systems: iOS, Android and Windows Phone platform. The project was performed in Chile, cover all the main cities. For example: Santiago, Rancagua, Antofagasta and Viña.
300 speakers were recorded in total, and each speaker recorded in a quiet environment.
The prompts were the phonetically rich sentences. The raw sentences are all selected from the News domain Twitter/Forum and SMS. We did remove a number of sentences that includes offensive or negative words or phrase. Finally, we had 108055 unique sentences in our list of sentences, that we generated the prompt sheets from with no more than 3 times for each.
With discarding some unqualified utterances, the whole corpus contains the recordings of 268,704 utterances; the pure recording time is about 519 hours (including leading silence and tail silence). The total size of this database is about 55.8 G.

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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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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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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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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We are happy to announce that 1 new Written Corpus and 1 new Terminological Resource are now available in our catalogue.

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*****************************************************************
ELRA - Language Resources Catalogue - Update
*****************************************************************

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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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:

• DGT-Acquis, ISLRN: 393-866-130-658-2
• DGT-TM, ISLRN: 710-653-952-884-4
• EAC-TM, ISLRN: 589-927-543-547-4
• ECDC-TM, ISLRN: 476-596-396-497-8
• English sentiment quotes, ISLRN: 574-735-957-886-6
• JRC-Acquis, ISLRN: 821-325-977-001-1
• JRC-Names, ISLRN: 328-863-023-410-2
• Multilingual summary evaluation data, ISLRN: 762-292-165-648-8
• Turkish Tweet Named Entity annotation, ISLRN: 764-177-227-350-7

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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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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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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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.info,  www.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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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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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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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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    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.
   
   

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

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