In this newsletter:
Fall 2020 Data Scholarship Recipients
Membership Year 2021 Publication Preview
LDC data and commercial technology development

New Publications:
Global TIMIT Learner Treebank English
Corpus of Law, Academic, and News
IARPA Babel Mongolian Language Pack IARPA-babel401b-v2.0b

Fall 2020 data scholarship recipients
Congratulations to the recipients of LDC's Fall 2020 data scholarships:

Nicole Dodd: University of California, Davis (USA); MA, Linguistics. Nicole is awarded a copy of Arabic Treebank Part 3 v. 3.2 LDC2010T08 for her research in relative clause processing in Standard Arabic.

Satwik Dutta: University of Texas at Dallas (USA); PhD, Electrical Engineering. Satwik is awarded copies of The CMU Kids Corpus LDC97263 and CLSU: Kids’ Speech Version 1.1. LDC2007S18 for his work in speech activity detection.

Pedram Hosseini: George Washington University (USA); PhD., Computer Science. Pedram is awarded copies of Penn Discourse Treebank Version 3.0 LDC2019T05 and The New York Times Annotated Corpus LDC2008T19 for his research in automatic detection of causal relations in text.

Mariano Maisonnave: Universidad Nacional del Sur (Argentina); PhD, Computer Science. Mariano is awarded a copy of ACE 2005 Multilingual Training Corpus LDC2006T06 for his work in event extraction.

Mark Sullivan: California State University, Los Angeles (USA); Masters, Applied and Advanced Studies in Education. Mark is awarded a copy of ETS Corpus of Non-Native Written English LDC2014T06 for his research in sentence boundary problems of Chinese L1 speakers in English compositions.

For information about the program, visit the Data Scholarships page.

Membership Year 2021 publication preview
The 2021 Membership Year is just around the corner and plans for next year’s publications are in progress. Among the expected releases are:

• Global TIMIT Mandarin Chinese: 6,000 linguistically rich utterances featuring time-aligned lexical and phonetic transcription
• Columbia Games Corpus: 12 spontaneous task-oriented dyadic conversations elicited from native Standard American English speakers playing computer games, transcribed and annotated for discourse/pragmatic phenomena
• My Science Tutor Children’s Conversational Speech: 400+ hours of speech from 1,371 US third, fourth, and fifth grade students participating in sessions with a virtual science tutor, transcripts included
• The SSNCE Database of Tamil Dysarthric Speech: Tamil speech from 20 dysarthric speakers aged 12-40 years and a control group (10 speakers) with time-aligned phonetic transcripts
• Icelandic Parliamentary Speech: 6,493 Icelandic Parliament recordings from 2005-2016 with 196 speakers, aligned and segmented and divided into training, development, and evaluation sets for ASR development
• LORELEI: representative and incident language packs containing monolingual text, bi-text, translations, annotations, supplemental resources, and related tools (Akan, Kinyarwanda, and Wolof)
• BOLT: co-reference, treebank, propbank, and translation resources for discussion forum, SMS/Chat, and conversational telephone speech data in all languages (Chinese, Egyptian Arabic, and English)
• TAC KBP: training and evaluation data for English surprise slot filling (2010) and English sentiment slot filling (2013-2014) tasks

Check your inbox in the coming weeks for more information about membership renewal. 

LDC data and commercial technology development
For-profit organizations are reminded that an LDC membership is a pre-requisite for obtaining a commercial license to almost all LDC databases. Non-member organizations, including non-member for-profit organizations, cannot use LDC data to develop or test products for commercialization, nor can they use LDC data in any commercial product or for any commercial purpose. LDC data users should consult corpus-specific license agreements for limitations on the use of certain corpora. Visit the Licensing page for further information.

New publications:
(1) Global TIMIT Learner Treebank English was developed by LDC and LAIX Inc. and consists of approximately 24 hours of L1 and L2 English read speech and transcripts. It is comprised of two separate data sets of 50 speakers reading 120 sentences from Treebank-3 (LDC99T42). Among the 120 sentences, 20 sentences were read by all speakers, 40 sentences were read by 10 speakers, and 60 sentences were read by one speaker, for a total of 3220 sentence types. 

L1 English Treebank was recorded at the University of Pennsylvania, USA; participants were 25 female and 25 male native American English speakers. L2 English Treebank was recorded at LAIX Inc., Shanghai, China. L2 speakers (25 female, 25 male) were Chinese learners of English considered fluent and who had passed specified standards on English assessment tests.      

The Global TIMIT project aimed to create a series of corpora in a variety of languages with a similar set of key features as in the original TIMIT Acoustic-Phonetic Continuous Speech Corpus (LDC93S1) which was designed for acoustic-phonetic studies and for the development and evaluation of automatic speech recognition systems. Specifically, those features include:

• A large number of fluently-read sentences, containing a representative sample of phonetic, lexical, syntactic, semantic, and pragmatic patterns
• A relatively large number of speakers
• Time-aligned lexical and phonetic transcription of all utterances
• Some sentences read by all speakers, others read by a few speakers, and others read by just one speaker

Global TIMIT Learner Treebank English is distributed via web download.  

2020 Subscription Members will automatically receive copies of this corpus. 2020 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for $750.

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(2) Corpus of Law, Academic and News consists of 400 Persian documents divided into three genres: legal, academic, and news. The legal section contains texts from official publications, including the civil penal code, the criminal penal code, and the constitution of the Islamic Republic of Iran. The academic sub-corpus is comprised of published academic abstracts in various disciplinary areas, such as Art and Humanities, Social Sciences, and Natural Sciences. The news sub-corpus was extracted from an archive of ten Iranian news outlets spanning the period 2010- 2020.

Each document contains metadata in the file's header with information such as specific text type, dates, and source, and also contains annotations marking title and body paragraphs. 

Corpus of Law, Academic and News is distributed via web download.

2020 Subscription Members will automatically receive copies of this corpus provided they have submitted a completed copy of the special license agreement. 2020 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for $100.

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(3) IARPA Babel Mongolian Language Pack IARPA-babel401b-v2.0b was developed by Appen for the IARPA (Intelligence Advanced Research Projects Activity) Babel program. It contains approximately 204 hours of Halh Mongolian conversational and scripted telephone speech collected in 2014 along with corresponding transcripts. The gender distribution among speakers is approximately equal; speakers' ages range from 16 years to 61 years. Calls were made using different telephones (e.g., mobile, landline) from a variety of environments including the street, a home or office, a public place, and inside a vehicle.

The Babel program focused on underserved languages and sought to develop speech recognition technology that could be rapidly applied to any human language to support keyword search performance over large amounts of recorded speech. 

This is the last release in the IARPA Babel series which consists of 25 language packs in total.

IARPA Babel Mongolian Language Pack IARPA-babel-401b-v2.0b is distributed via web download.

2020 Subscription Members will automatically receive copies of this corpus provided they have submitted a completed copy of the special license agreement. 2020 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for $25.

Membership Coordinator

Linguistic Data Consortium

University of Pennsylvania

T: +1-215-573-1275

E: ldc@ldc.upenn.edu

M: 3600 Market St. Suite 810

      Philadelphia, PA 19104

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

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

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Fearless Steps Corpus

John H.L. Hansen, Abhijeet Sangwan, Lakshmish Kaushik, Chengzhu Yu Center for Robust Speech Systems (CRSS), Eric Jonsson School of Engineering, The University of Texas at Dallas (UTD), Richardson, Texas, U.S.A.

NASA’s Apollo program is a great achievement of mankind in the 20th century. CRSS, UT-Dallas has undertaken an enormous Apollo data digitization initiative where we proposed to digitize Apollo mission speech data (~100,000 hours) and develop Spoken Language Technology based algorithms to analyze and understand various aspects of conversational speech. Towards achieving this goal, a new 30 track analog audio decoder is designed to decode 30 track Apollo analog tapes and is mounted on to the NASA Soundscriber analog audio decoder (in place of single channel decoder). Using the new decoder all 30 channels of data can be decoded simultaneously thereby reducing the digitization time significantly. 
We have digitized 19,000 hours of data from Apollo missions (including entire Apollo-11, most of Apollo-13, Apollo-1, and Gemini-8 missions). This audio archive is named as “Fearless Steps Corpus”. This is one of the most unique and singularly large naturalistic audio corpus of such magnitude. Automated transcripts are generated by building Apollo mission specific custom Deep Neural Networks (DNN) based Automatic Speech Recognition (ASR) system along with Apollo mission specific language models. Speaker Identification System (SID) to identify the speakers are designed. A complete diarization pipeline is established to study and develop various SLT tasks. 
We will release this corpus for public usage as a part of public outreach and promote SLT community to utilize this opportunity to build naturalistic spoken language technology systems. The data provides ample opportunity setup challenging tasks in various SLT areas. As a part of this outreach we will be setting “Fearless Challenge” in the upcoming INTERSPEECH 2018. We will define and propose 5 tasks as a part of this challenge. The guidelines and challenge data will be released in the Spring 2018 and will be available for download for free. The five challenges are, (1) Automatic Speech Recognition (2) Speaker Identification (3) Speech Activity Detection (4) Speaker Diarization (5) Keyword spotting and Joint Topic/Sentiment detection.
Looking forward for your participation (John.Hansen@utdallas.edu) 

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OPENGLOT –An open environment for the evaluation of glottal inverse filtering

OPENGLOT is a publically available database that was designed primarily for the evaluation of glottal inverse filtering algorithms. In addition, the database can be used in evaluating formant estimation methods. OPENGLOT consists of four repositories. Repository I contains synthetic glottal flow waveforms, and speech signals generated by using the Liljencrants–Fant (LF) waveform as an excitation, and an all-pole vocal tract model. Repository II contains glottal flow and speech pressure signals generated using physical modelling of human speech production. Repository III contains pairs of glottal excitation and speech pressure signal generated by exciting 3D printed plastic vocal tract replica with LF excitations via a loudspeaker. Finally, Repository IV contains multichannel recordings (speech pressure signal, EGG, high-speed video of the vocal folds) from natural production of speech.

OPENGLOT is available at:

http://research.spa.aalto.fi/projects/openglot/

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Nous sommes heureux de vous annoncer la publication d¹un ouvrage consacré
au treebank Rhapsodie, un corpus de français parlé de 33 000 mots
finement annoté en prosodie et en syntaxe.

Accès à la publication : https://benjamins.com/catalog/scl.89 (voir flyer
ci-joint)

Accès au treebank : https://www.projet-rhapsodie.fr/
Les données librement accessibles sont diffusées sous licence Creative
Commons.
Le site donne également accès aux guides d¹annotations.

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The My Science Tutor Children?s Conversational Speech Corpus (MyST Corpus) is the world?s largest English children?s speech corpus.  It is freely available to the research community for research use.  Companies can acquire the corpus for $10,000.  The MyST Corpus was collected over a 10-year period, with support from over $9 million in grants from the US National Science Foundation and Department of Education, awarded to Boulder Learning Inc. (Wayne Ward, Principal Investigator).

The MyST corpus contains speech collected from 1,374 third, fourth and fifth grade students.  The students engaged in spoken dialogs with a virtual science tutor in 8 areas of science.  A total of 11,398 student sessions of 15 to 20 minutes produced a total of 244,069 utterances.  42% of the utterances have been transcribed at the word level.  The corpus is partitioned into training and test sets to support comparison of research results across labs. All parents and students signed consent forms, approved by the University of Colorado?s Institutional Review Board,  that authorize distribution of the corpus for research and commercial use. 

The MyST children?s speech corpus contains approximately ten times as many spoken utterances as all other English children?s speech corpora combined (see https://en.wikipedia.org/wiki/List_of_children%27s_speech_corpora). 

Additional information about the corpus, and instructions for how to acquire the corpus (and samples of the speech data) can be found on the Boulder Learning Web site at http://boulderlearning.com/request-the-myst-corpus/.   

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• HARVARD speech corpus - native British English speaker, digital re-recording

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Magic Data Technology Kid Voice TTS Corpus in Mandarin Chinese

Magic Data Technology is one of the leading artificial intelligence data service providers in the world. The company is committed to providing a wild range of customized data services in the fields of speech recognition, intelligent imaging and Natural Language Understanding.

This corpus was recorded by a four-year-old Chinese girl originally born in Beijing China. This time we published 15-minute speech data from the corpus for non-commercial use.

The contents and the corresponding descriptions of the corpus:

• The corpus contains 15 minutes of speech data, which is recorded in NC-20 acoustic studio.

• The speaker is 4 years old originally born in Beijing

• Detail information such as speech data coding and speaker information is preserved in the metadata file.

• This corpus is natural kid style.

• Annotation includes four parts: pronunciation proofreading, prosody labeling, phone boundary labeling and POS Tagging.

• The annotation accuracy is higher than 99%.

• For phone labeling, the database contains the annotation not only on the boundary of phonemes, but also on the boundary of the silence parts.

The corpus aims to help researchers in the TTS fields. And it is part of a much bigger dataset (2.3 hours MAGICDATA Kid Voice TTS Corpus in Mandarin Chinese) which was recorded in the same environment. This is the first time to publish this voice!

Please note that this corpus has got the speaker and her parents’ authorization.

Samples are available.

Do not hesitate to contact us for any questions.

Website: http://www.imagicdatatech.com/index.php/home/dataopensource/data_info/id/360

E-mail: business@magicdatatech.com

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ELRA-S0408 Speechtera Pronunciation Dictionary

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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Paris, France, April 23, 2020

ELRA is happy to announce that Language Resources collected within the ELRC Network, funded by the European Commission, are now available from the ELRA Catalogue of Language Resources.

In total, 180 Written Corpora, 5 Multilingual Lexicons and 2 Terminological Resources, are freely available under open licences and can be downloaded directly from the catalogue. Type 'ELRC' in the catalogue search engine (http://catalog.elra.info/en-us/repository/search/?q=ELRC) to access and download resources.

All these Language Resources can be used to support your Machine Translation solutions developments. They cover the official languages of the European Union and CEF associated countries.

More LRs coming from ELRC will be added as they become available.

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About ELRC
ELRC (European Language Resources Coordination) Network raises awareness and promote the acquisition and continued identification and collection of language resources in all official languages of the EU and CEF associated countries. These activities aim to help to improve the quality, coverage and performance of automated translation solutions in the context of current and future CEF digital services.

To find out more about ELRC, please visit the website: http://lr-coordination.eu


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. Language Resources covering various fields of HLT (including Multimodal, Speech, Written, Terminology) and a great number of languages are available from the ELRA catalogue. ELRA's strong involvement in the fields of Language Resources  and Language Technologies is also emphasized at the LREC conference, organized every other year since 1998.

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

For more information on the catalogue, please contact Valérie Mapelli
If you would like to enquire about having your resources distributed by ELRA, please do not hesitate to contact us.

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

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Press Release - Immediate
Paris, France, May 4, 2020

ELRA and SpeechOcean signed a new Language Resources distribution agreement. On behalf of ELRA, ELDA acts as the distribution agency for SpeechOcean since 2007 and incorporated 46 new speech resources to the ELRA Catalogue of Language Resources catalogue.

Those resources were designed and collected to boost Speech Recognition. They cover the following languages:

• Chinese-Mandarin,
• French from France and Canada,
• German,
• Italian,
• Hong Kong Cantonese,
• Japanese,
• Korean,
• Pashto,
• Portuguese from Portugal and Brazil,
• Russian,
• Spanish from US and Mexico,
• Taiwanese,
• Several variants of English (English from Australia, Canada, China, Japan, Korea, United Kingdom, USA)

This new set of speech LRs leads to a total of 103 LRs distributed by ELRA on behalf of SpeechOcean, and aims to strengthen ELRA's position as the leading worldwide distribution centre. With this agreement SpeechOcean will get more visibility in particular on the European market.

The detailed list of all 103 Language Resources from SpeechOcean is available here: http://catalog.elra.info/en-us/repository/search/?q=S0228

About SpeechOcean
Since its establishment as an AI data resource provider, Speechocean has always devoted itself to providing specialized engineering data products and services to enterprises and scientific research institutions in the whole industry chain of AI. Our business involves various domains such as speech recognition, speech synthesis, computer vision, lexicon, and natural language processing and provides relevant services for the design, collection, transcription, annotation, etc. of data.

To find out more about SpeechOcean, please visit the website: http://www.speechocean.com

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. Language Resources covering various fields of HLT (including Multimodal, Speech, Written, Terminology) and a great number of languages are available from the ELRA catalogue. ELRA's strong involvement in the fields of Language Resources  and Language Technologies is also emphasized at the LREC conference, organized every other year since 1998.

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

For more information on the catalogue, please contact Valérie Mapelli

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

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

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ELRA recognises the importance of sharing Language Resources (LRs) and making them available to the community.

Since the 2014 edition of LREC, the Language Resources and Evaluation Conference, participants have been offered the possibility to share their LRs (data, tools, web-services, etc.) when submitting a paper, uploading them in a special LREC repository set up by ELRA. This effort of sharing LRs, linked to the LRE Map initiative (https://lremap.elra.info) for their description, contributes to creating a common repository where everyone can deposit and share data.

The LREC initiative 'Share your LRs' was launched in 2014 in Reykjavik. It was successfully continued in 2016 in Portoro? and 2018 in Miyazaki.

Corresponding repositories are available here:

• 125 LRs shared in 2018 are available at https://bit.ly/3dpWdq3
• 82 LRs shared in 2016 are available at http://ow.ly/KTzf30fXoCe
• 120 LRs shared in 2014 are available at http://ow.ly/9gDm30fVMiu

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ELRA announces that MEDIA data are now available for free for academic research

Further to the request of the HLT French community to foster evaluation activities for man-machine dialogue systems for French language, ELRA has decided to provide a free access to the MEDIA speech corpora and evaluation package for academic research purposes.

The MEDIA data can be found in the ELRA Catalogue under the following references:

• ELRA-E0024  MEDIA Evaluation Package

•  ELRA-S0272 MEDIA speech database for French
  

• ELRA-S0371 PortMedia French and Italian corpus
  

Data available from the ELRA Catalogue can be obtained easily by contacting ELRA.  

The MEDIA project was carried out within the framework of Technolangue, the French national research programme funded by the French Ministry of Research and New Technologies (MRNT) with the objective of running a campaign for the evaluation of man-machine dialogue systems for French. The campaign was distributed over two actions: an evaluation taking into account the dialogue context and an evaluation not taking into account the dialogue context.

PortMedia was a follow up project supported by the French Research Agency (ANR). The French and Italian corpus was produced by ELDA, with the same paradigm and specifications as the MEDIA speech database but on a different domain.

For more information and/or questions, please write to contact@elda.org.

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

To find out more about ELRA and its respective catalogue, please visit: http://www.elra.info and http://catalogue.elra.info

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