In this newsletter:
LDC adds DOI Identifier to its Language Resources
Fall 2020 LDC Data Scholarship Program

New Publications:
LORELEI Vietnamese Representative Language Pack
DEFT Chinese Light and Rich ERE Annotation
CALLFRIEND American English – Southern Dialect Second Edition

LDC adds DOI Identifier to its Language Resources
As of July 2020, LDC’s language resources include a Digital Object Identifier (DOI), an internationally recognized identification standard for online digital material. DOIs are alpha numeric strings that correspond to URLs and metadata for specified resources. They are expressed as links that resolve to the object’s online location. For example, the DOI for Penn Parsed Corpora of Historical English LDC2020T16 is https://doi.org/10.35111/4hzx-5483, which leads users to the LDC catalog entry for this data set. To facilitate its assignment and administration of DOIs, LDC has joined DataCite, a global DOI provider for research data. (DOIs for resources released before July 2020 will be assigned through a process expected to be completed shortly.) LDC data sets now have four persistent identifiers: a unique LDC number, ISBN, ISLRN, and DOI. Adding DOIs is consistent with our aim to follow best practices for archiving and curating digital resources, evidenced by the CoreTrustSeal certification which recognizes the LDC Catalog as a trustworthy data repository.

Fall 2020 LDC Data Scholarship Program
Student applications for the Fall 2020 LDC Data Scholarship program are being accepted now through September 15, 2020. This scholarship program provides eligible students with no-cost access to LDC data. Students must complete an application consisting of a data use proposal and letter of support from their advisor.

For application requirements and program rules, visit the LDC Data Scholarship page.

New publications:
(1) LORELEI Vietnamese Representative Language Pack consists of Vietnamese monolingual text, Vietnamese-English parallel text, annotations, supplemental resources, and related software tools developed by LDC for the DARPA LORELEI program.

The LORELEI (Low Resource Languages for Emergent Incidents) program was concerned with building human language technology for low resource languages in the context of emergent situations like natural disasters or disease outbreaks. Linguistic resources for LORELEI include Representative Language Packs and Incident Language Packs for over two dozen low resource languages, comprising data, annotations, basic natural language processing tools, lexicons, and grammatical resources. Representative languages were selected to provide broad typological coverage, while incident languages were selected to evaluate system performance on a language whose identity was disclosed at the start of the evaluation.

Data was collected in the following genres: discussion forum, news, reference, social network, and weblogs. Data volumes are as follows:

• Over 172 million words of Vietnamese monolingual text, approximately 325,000 words of which were translated into English
• 106,000 Vietnamese words translated from English data
• 1.9 million words of found parallel text

Approximately 75,000 words were annotated for named entities and up to 25,000 words contain additional annotation, including situation frames (identifying entities, needs, and issues) and entity linking and detection.

LORELEI Vietnamese Representative Language Pack 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 a $250.

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(2) DEFT Chinese Light and Rich ERE Annotation contains Chinese discussion forum web text annotated for entities, relations, and events (ERE) using the ERE Light and ERE Rich annotations schemas developed by LDC. Light ERE annotation labels entity mentions for the target set of ERE types between and among those entities, including coreference. Rich ERE annotation expands types and tagging for ERE annotation tasks and replaces event coreference with event hopper annotation. All files in this release (157) were annotated following Light ERE guidelines; a subset (149) were also labeled with Rich ERE annotation. 

DARPA’s Deep Exploration and Filtering of Text (DEFT) program aimed to address remaining capability gaps in state-of-the-art natural language processing technologies related to inference, causal relationships, and anomaly detection. LDC supported the DEFT program by collecting, creating, and annotating a variety of data sources.

DEFT Chinese Light and Rich ERE Annotation 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 $2000.

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(3) CALLFRIEND American English – Southern Dialect Second Edition was developed by LDC and consists of approximately 26 hours of unscripted telephone conversations between native speakers of Southern dialects of American English. This second edition updates the audio files to wav format, simplifies the directory structure, and adds documentation and metadata. The first edition is available as CALLFRIEND American English-Southern Dialect (LDC96S47).

The CALLFRIEND collection was conducted by LDC in support of language identification technology development. All data in this release was collected before July 1997. Participants could speak with a person of their choice on any topic; most called family members and friends. All calls originated in North America. The recorded conversations last up to 30 minutes.

CALLFRIEND American English – Southern Dialect Second Edition 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 $1000.

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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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