ISCA - International Speech
Communication Association


ISCApad Archive  »  2014  »  ISCApad #194  »  Resources

ISCApad #194

Monday, August 04, 2014 by Chris Wellekens

5 Resources
5-1 Books
5-1-1Tuomas Virtanen, Rita Singh, Bhiksha Raj (editors),Techniques for Noise Robustness in Automatic Speech Recognition,Wiley

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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5-1-2Niebuhr, Olivier, Understanding Prosody:The Role of Context, Function and Communication

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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5-1-3Albert Di Cristo: « La Prosodie de la Parole : Une Introduction », Editions de Boeck-Solal (296 p)
 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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5-1-4Pierre-Yves Oudeyer, 'Aux sources de la parole: auto-organisation et évolution', Odile Jacob
Pierre-Yves Oudeyer, dir. rech. Inria, vient de publier 'Aux sources de la parole: auto-organisation et évolution', chez Odile Jacob (Sept. 2013).
 
Il discute de la question de l'évolution et de l'acquisition de la parole, chez l'enfant et chez les robots.
 
En faisant dialoguer biologie, linguistique, neurosciences et expériences robotiques, 
ce livre étudie en particulier les phénomènes d'auto-organisation, permettant la formation spontanée de langues nouvelles dans une population d'individus. 
Il présente en particulier des expériences dans lesquelles une population de robots numériques invente, forme, et négotie son propre système de parole
et explique comment de telles expériences robotiques peuvent nous aider à mieux comprendre l'homme.
 
Il présente aussi des expérimentations robotiques récentes, et à partir de perspectives nouvelles en intelligence artificielle, dans lesquelles des mécanismes de curiosité permettent à un robot de découvrir par lui-même son corps, les objets qui l'entourent, et finalement les interactions vocales avec ses pairs. C'est ainsi que s'auto-organise son propre développement cognitif, et qu'apparaissent des hypothèses nouvelles pour comprendre le développement chez l'enfant.
 
Site web du livre: http://goo.gl/A6EwTJ
 
 
 
Pierre-Yves Oudeyer,
Directeur de recherche, Inria
Responsable de l'équipe Flowers
Inria Bordeaux Sud-Ouest et Ensta-ParisTech, France
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5-1-5Björn 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
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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5-1-6Li 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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5-2 Database
5-2-1ELRA - Language Resources Catalogue - Update (2014-07)


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ELRA - Language Resources Catalogue - Update
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We are happy to announce that 3 new Speech resources are now available in our catalogue. 

ELRA-S0366 LECTRA (LECture TRAnscriptions in European Portuguese)
This corpus is composed of the audio and the manual transcriptions from seven 1-semester University courses in Portuguese. The corpus contains a total of 28 hours of audio speech that were manually transcribed by several trained annotators. The corpus is comprised of technical University lectures.
For more information, see: http://catalog.elra.info/product_info.php?products_id=1221

ELRA-S0367 CORAL Corpus
The CORAL Corpus is a collection of spoken dialogues in European Portuguese. It consists of 56 dialogues about a predetermined subject: maps. One of the participants (giver) has a map with some landmarks and a route drawn between them; the other (follower) has also landmarks, but no route and consequently must reconstruct it. Only orthographic transcription was done for the whole corpus. A pilot recording was annotated in several levels.
For more information, see: http://catalog.elra.info/product_info.php?products_id=1222

ELRA-S0370 MoveOn Speech and Noise Corpus
The MoveOn Speech and Noise Corpus is a corpus recorded under the extreme conditions of the motorcycle environment within the MoveOn project. The speech utterances are in British English approaching the issue of command and control and template driven dialog systems with a focus on – but not limited to - the police domain. The major part of the corpus comprises noisy speech and  environmental noise recorded on a motorcycle. Several clean speech recording sessions with the same recording setup (including the motorcycle helmet) in an office environment complete the corpus.
For more information, see: http://catalog.elra.info/product_info.php?products_id=1223


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

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/LRs-Announcements.html    
 

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5-2-2ELRA releases free Language Resources

ELRA releases free Language Resources
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Anticipating users’ expectations, ELRA has decided to offer a large number of resources for free for Academic research use. Such an offer consists of several sets of speech, text and multimodal resources that are regularly released, for free, as soon as legal aspects are cleared. A first set was released in May 2012 at the occasion of LREC 2012. A second set is now being released.

Whenever this is permitted by our licences, please feel free to use these resources for deriving new resources and depositing them with the ELRA catalogue for community re-use.

Over the last decade, ELRA has compiled a large list of resources into its Catalogue of LRs. ELRA has negotiated distribution rights with the LR owners and made such resources available under fair conditions and within a clear legal framework. Following this initiative, ELRA has also worked on LR discovery and identification with a dedicated team which investigated and listed existing and valuable resources in its 'Universal Catalogue', a list of resources that could be negotiated on a case-by-case basis. At LREC 2010, ELRA introduced the LRE Map, an inventory of LRs, whether developed or used, that were described in LREC papers. This huge inventory listed by the authors themselves constitutes the first 'community-built' catalogue of existing or emerging resources, constantly enriched and updated at major conferences.

Considering the latest trends on easing the sharing of LRs, from both legal and commercial points of view, ELRA is taking a major role in META-SHARE, a large European open infrastructure for sharing LRs. This infrastructure will allow LR owners, providers and distributors to distribute their LRs through an additional and cost-effective channel.

To obtain the available sets of LRs, please visit the web page below and follow the instructions given online:
http://www.elra.info/Free-LRs,26.html

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5-2-3LDC Newsletter (July 2014)

In this newsletter:

Fall 2014 Data Scholarship Program  -

New publications:

2009 NIST Language Recognition Evaluation Test Set  -

GALE Arabic-English Word Alignment Training Part 3 -- Web  -

GALE Phase 2 Chinese Newswire Parallel Text Part 1  -


Fall 2014 Data Scholarship Program

Applications are now being accepted through Monday, September 15, 2014, 11:59PM EST for the Fall 2014 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) 2009 NIST Language Recognition Evaluation Test Set contains approximately 215 hours of conversational telephone speech and radio broadcast conversation collected by LDC in the following 23 languages and dialects: Amharic, Bosnian, Cantonese, Creole (Haitian), Croatian, Dari, English (American), English (Indian), Farsi, French, Georgian, Hausa, Hindi, Korean, Mandarin, Pashto, Portuguese, Russian, Spanish, Turkish, Ukrainian, Urdu and Vietnamese.

The goal of the NIST (National Institute of Standards and Technology) Language Recognition Evaluation (LRE) is to establish the baseline of current performance capability for language recognition of conversational telephone speech and to lay the groundwork for further research efforts in the field. NIST conducted language recognition evaluations in 1996, 2003, 2005 and 2007. The 2009 evaluation increased the number of target languages. Most of the test data originated from multilingual Voice of America (VOA) radio broadcasts assessed as being of telephone bandwidth in addition to conversational telephone speech. Further information regarding this evaluation can be found in the evaluation plan which is included in the documentation for this release.

LDC released the prior LREs as:

2003 NIST Language Recognition Evaluation (LDC2006S31)

2005 NIST Language Recognition Evaluation (LDC2008S05)

2007 NIST Language Recognition Evaluation Test Set (LDC2009S04)

2007 NIST Language Recognition Evaluation Supplemental Training Set (LDC2009S05)

The VOA speech data was collected by LDC in 2000 and 2001 and constitutes approximately 75% of the test set. The telephone speech was taken from LDC's Mixer 3 collection recorded between 2005 and 2007.

All test speech segments are presented as a sampled data stream in standard 8-bit 8-kHz μ-law format. Each segment is stored separately in a single channel SPHERE format file. The test segments contain three nominal durations of speech: 3 seconds, 10 seconds and 30 seconds. Actual speech durations vary, but were constrained to be within the ranges of 2-4 seconds, 7-13 seconds and 23-35 seconds, respectively.

2009 NIST Language Recognition Evaluation Test Set is distributed on 2 DVD-ROM.

2014 Subscription Members will automatically receive two copies of this data.  2014 Standard Members may request a copy as part of their 16 free membership corpora.  Non-members may license this data for US$2000.

 

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(2) GALE Arabic-English Word Alignment Training Part 3 -- Web was developed by LDC and contains 217,158 tokens of word aligned Arabic and English parallel text enriched with linguistic tags. This material was used as training data in the DARPA GALE (Global Autonomous Language Exploitation) program.

Some approaches to statistical machine translation include the incorporation of linguistic knowledge in word aligned text as a means to improve automatic word alignment and machine translation quality. This is accomplished with two annotation schemes: alignment and tagging. Alignment identifies minimum translation units and translation relations by using minimum-match and attachment annotation approaches. A set of word tags and alignment link tags are designed in the tagging scheme to describe these translation units and relations. Tagging adds contextual, syntactic and language-specific features to the alignment annotation.

Other releases available in this series are:

GALE Chinese-English Word Alignment and Tagging Training Part 1 -- Newswire and Web (LDC2012T16)

GALE Chinese-English Word Alignment and Tagging Training Part 2 -- Newswire (LDC2012T20)

GALE Chinese-English Word Alignment and Tagging Training Part 3 -- Web (LDC2012T24)

GALE Chinese-English Word Alignment and Tagging Training Part 4 -- Web (LDC2013T05)

GALE Chinese-English Word Alignment and Tagging -- Broadcast Training Part 1 (LDC2013T23)

GALE Arabic-English Word Alignment Training Part 1 -- Newswire and Web (LDC2014T05)

GALE Arabic-English Word Alignment Training Part 2 -- Newswire (LDC2014T10)

This release consists of Arabic source web data collected by LDC. The distribution by genre, words, character tokens and segments appears below:

Language

Genre

Files

Words

CharTokens

Segments

Arabic

WB

2,449

154,144

217,158

7,332

Note that word count is based on the untokenized Arabic source, and token count is based on the tokenized Arabic source.

The Arabic word alignment tasks consisted of the following components:

Normalizing tokenized tokens as needed

Identifying different types of links

Identifying sentence segments not suitable for annotation

Tagging unmatched words attached to other words or phrases

GALE Arabic-English Word Alignment Training Part 3 -- Web is distributed via web download.

2014 Subscription Members will automatically receive two copies of this data on disc.  2014 Standard Members may request a copy as part of their 16 free membership corpora.  Non-members may license this data for US$1750.

 

*

(3) GALE Phase 2 Chinese Newswire Parallel Text Part 1 was developed by LDC. Along with other corpora, the parallel text in this release comprised training data for Phase 2 of the DARPA GALE (Global Autonomous Language Exploitation) Program. This corpus contains 117,173 tokens of Chinese source text and corresponding English translations selected from newswire data collected by LDC in 2007 and transcribed by LDC or under its direction.

This release includes 167 source-translation document pairs, comprising 117,173 tokens of translated data. Data is drawn from four distinct Chinese newswire sources: China News Service, Guangming Daily, People's Daily and People's Liberation Army Daily.

The data was transcribed by LDC staff and/or transcription vendors under contract to LDC in accordance with Quick Rich Transcription guidelines developed by LDC. Transcribers indicated sentence boundaries in addition to transcribing the text. Data was manually selected for translation according to several criteria, including linguistic features, transcription features and topic features. The transcribed and segmented files were then reformatted into a human-readable translation format and assigned to translation vendors. Translators followed LDC's Chinese to English translation guidelines. Bilingual LDC staff performed quality control procedures on the completed translations.

Source data and translations are distributed in TDF format. TDF files are tab-delimited files containing one segment of text along with meta information about that segment. Each field in the TDF file is described in TDF_format.text. All data are encoded in UTF-8.

GALE Phase 2 Chinese Newswire Parallel Text Part 1 is distributed via web download.

2014 Subscription Members will automatically receive two copies of this data on disc.  2014 Standard Members may request a copy as part of their 16 free membership corpora.  Non-members may license this data for US$1750.
 

 


 

 

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5-2-4Appen 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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5-2-5OFROM 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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5-2-6Real-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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5-2-7Aide 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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5-2-8Rhapsodie: 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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5-2-9COVAREP: 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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5-2-10Annotation 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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5-2-11French 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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5-2-12Google '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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5-2-13International 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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5-2-14ISLRN 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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5-2-15Speechocean – update (July 2014)

Speechocean – update (July 2014):

 

Speechocean: A global language resources and data services supplier

Speechocean has over 500 large-scale databases available in 110+ languages and accents with the platform of desktop, in-car, telephony and tablet PC. Our data repository is enormous and diversified, which includes ASR Databases, TTS Databases, Lexica, Text Corpora, etc.

Speechocean is glad to announce more resources that have been released:

ASR Databases

Speechocean provides 110+ regional languages corpora, available in a variety of formats, situational styles, scene environments and platform systems, covering In-car speech recognition corpora, mobile phone speech recognition corpora, fixed-line speech recognition corpora, desktop speech recognition corpora, etc. This month we released more European languages (Part One) databases which were made for the tuning and testing purpose of speech recognition systems for speech ASR applications.

    1. In-Car

Serial Number

Kingline Data Names

Sound Parameter

Utterances

King-ASR-147

Italian Speech Recognition Corpus
( in car ) 300 Speakers

16 K16 bit
Four Channels

360230

King-ASR-153

Russian Speech Recognition Corpus
( in car) 308 Speakers

16 K16 bit
Four Channels

392,200

King-ASR-157

Polish Speech Recognition Corpus
( in car) 300 Speakers

16 K16 bit
Four Channels

356000

King-ASR-162

Dutch Speech Recognition Corpus
(in car) 300 Speakers

16 K16 bit
Four Channels

360030

King-ASR-170

Danish Speech Recognition Corpus
(in car) 300 Speakers

16 K16 bit
Four Channels

360058

King-ASR-172

Brazilian Portuguese Speech Recognition Corpus
( in car) 300 Speakers

16 K16 bit
Four Channels

360020


Telephony

Serial Number

Kingline Data Names

Sound Parameter

Utterances

King-ASR-219

Spanish Speech Recognition Corpus (Telephone) Conversational 1000 speakers

8K,16bit
one Channel

300000

 

1.3 Mobile

Serial Number

Kingline Data Names

Sound Parameter

Utterances

King-ASR-149

Finnish Speech Recognition Corpus
(mobile) 200 speakers

8K,16bit
one channel

60000

King-ASR-154

Brazilian Portuguese Speech Recognition
Corpus (mobile) Sentence (301 Speakers)

16 K, 16 bit
one channel

90266

King-ASR-155

European Portuguese Speech Recognition Corpus (Mobile) 300 Speakers

16K,16bit
one channel

90000

King-ASR-205

Turkish Speech Recognition Corpus
(mobile) Sentence (302 Speakers)

16 K, 16 bit
one channel

99471

King-ASR-206

Greek Speech Recognition Corpus
(Mobile) 300 Speakers

22K,16bit
one channel

45000

King-ASR-209

Dutch Speech Recognition Corpus
(Mobile) 200 Speakers

16K,16bit
one channel

60000

    1. Desktop

      Serial Number

      Kingline Data Names

      Sound Parameter

      Utterances

      King-ASR-181

      Italian Speech Recognition Corpus
      (desktop) –Sentence 201 Speakers

      44.1K,16bit
      Four Channels

      240880

      King-ASR-212

      Polish Speech Recognition Corpus (Desktop) -Sentence (200 Speakers)

      44.1K,16bit
      Two Channels

      119948

      King-ASR-084

      Russian Speech Recognition Corpus (Desktop) –Comprehensive utterances (200 Speakers)

      44.1K,16bit
      Four Channels

      239936

      King-ASR-158

      Swedish Speech Recognition Corpus (Desktop) -Sentence (200 Speakers)

      44.1K,16bit
      Two Channels

      119938

      King-ASR-159

      Turkish Speech Recognition Corpus (Desktop) -Sentence (201 Speakers)

      44.1K,16bit
      Two Channels

      120578

  1. TTS Databases

Speechocean licenses a variety of databases in more than 40 languages for speech synthesis broadcasting speech, emotional speech, etc. which can be used in different algorithms.

Serial No.

Kingline Data Names

Sound Parameter

Utterances

Recording Hours

King-TTS-016

Italian Speech Synthesis Database (Male)

44.1K,20bit
Two Channels

7211

9.09

King-TTS-017

Portugal Portuguese Speech Synthesis Database (Female)

44.1K,21bit
Two Channels

9900

12.6

King-TTS-018

Portugal Portuguese Speech Synthesis Database (Male)

44.1K,22bit
Two Channels

5000

Under Building

King-TTS-019

Russian Speech Synthesis Database (Female)

44.1K,23bit
Two Channels

8143

14.59

King-TTS-020

Russian Speech Synthesis Database (Male)

44.1K,24bit
Two Channels

8216

12.32

King-TTS-021

Polish Speech Synthesis Database (Female)

44.1K,25bit
Two Channels

5000

Under Building

King-TTS-022

Turkish Speech Synthesis Database (Female)

44.1K,26bit
Two Channels

5000

Under Building

King-TTS-029

Ukrainian Speech Synthesis Database (Female)

44.1K,27bit
Two Channels

5000

Under Building

 

  1. Text Corpora

Speechocean licenses many kinds of text corpora in many languages which is superb for language model training.

ID

Kingline Data Names

 Languages

Size

King-NLP-027

Database of Arab Names

Arabic

7000000Words

King-NLP-028

Database of Arab Names in Arabic

Arabic

222000Words

King-NLP-029

Italian Personal Names Corpus

Italian

Under Building

King-NLP-030

Italian Spanish Address Corpus

Italian

Under Building

King-NLP-031

Portuguese Personal Names Corpus

Portuguese

Under Building

King-NLP-032

Portuguese Address Corpus

Portuguese

Under Building

King-NLP-033

Polish personal names corpus

Polish

Under Building

 

  1. Lexica

Speechocean builds pronunciation lexica in many languages which can be licensed to customers.

No.

Name

Phoneme Set

King-Lexicon-027

Czech Pronunciation Lexicon

SAMPA

King-Lexicon-028

Greek Pronunciation Lexicon

SAMPA

King-Lexicon-029

Hungarian Pronunciation Lexicon

SAMPA

King-Lexicon-031

Catalan Pronunciation Lexicon

UPC

King-Lexicon-036

Arabic Pronunciation Lexicon

Under Building

King-Lexicon-037

Brazilian Portuguese Pronunciation Lexicon

SAMPA

King-Lexicon-043

Norwegian Pronunciation Lexicon

XSAMPA

 

 

Contact Information

Xianfeng Cheng

Business Manager of Commercial Department

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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5-3 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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5-3-3Voice analysis toolkit
After just completing my PhD I have made the algorithms I have developed during it available online:  https://github.com/covarep/covarep
The so-called Voice Analysis Toolkit contains algorithms for glottal source and voice quality analysis. In making the code available online I hope that people in the speech processing community can benefit from it. I would really appreciate if you could include a link to this in the software section of the next ISCApad (section 5-3).
 
thanks for this.
John
 
--
Researcher
 
Phonetics and Speech Laboratory (Room 4074) Arts Block,
Centre for Language and Communication Studies,
School of Linguistics, Speech and Communication Sciences, Trinity College Dublin, College Green Dublin 2
Phone:    (+353) 1 896 1348 Website:  http://www.tcd.ie/slscs/postgraduate/phd-masters-research/student-pages/johnkane.php
Check out our workshop!! http://muster.ucd.ie/workshops/iast/
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5-3-4Bob 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,

    *       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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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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