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ISCApad #256

Tuesday, October 15, 2019 by Chris Wellekens

5-2 Database
5-2-1Linguistic Data Consortium (LDC) update (September 2019)

 

In this newsletter:
LDC at Interspeech 2019

New Publications:
CALLFRIEND Canadian French Second Edition

BOLT Chinese-English Word Alignment and Tagging -- SMS/Chat Training
Machine Reading Phase 1 NFL Scoring Training Data



LDC at Interspeech 2019
LDC is exhibiting at Interspeech 2019, September 15-19 in Graz, Austria. Stop by Booth F16 to learn more about recent developments at the Consortium and new publications.

Be on the lookout for The Second DIHARD Speech Diarization Challenge (DIHARD II), a special session co-organized by LDC, and the following presentations featuring LDC work:

The Second DIHARD Diarization Challenge: Dataset - task - and baselines
Neville Ryant, Christopher Cieri, Mark Liberman (LDC), Kenneth Church (Baidu, USA), Alejandrina Cristia (Laboratoire de Sciences Cognitives et Psycholinguistique), Jun Du (University of Science and Technology of China), Sriram Ganapathy (Indian Institute of Science)
Oral Session, Tuesday September 17, 10:00 – 10:20, Hall 3


Automatic Detection of Prosodic Focus in American English
Sunghye Cho and Mark Liberman (LDC), Yong-cheol Lee (Cheongju University)
Poster Session, Wednesday September 18, 16:00 – 18:00, Gallery B


Automatic detection of ASD in children using acoustic and text features from brief natural conversations
Sunghye Cho, Mark Liberman, Neville Ryant (LDC), Meredith Cola, Robert T. Schultz, Julia Parish-Morris (Children's Hospital of Philadelphia)
Oral Session, Wednesday September 18, 16:45 – 17:00, Hall 3


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

 


New publications:

(1) CALLFRIEND Canadian French Second Edition was developed by LDC and consists of approximately 26 hours of unscripted telephone conversations between native speakers of Canadian French. 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 Canadian French (LDC96S48).

All data 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 Canadian French Second Edition is distributed via web download.

2019 Subscription Members will automatically receive copies of this corpus. 2019 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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(2) BOLT Chinese-English Word Alignment and Tagging -- SMS/Chat Training was developed by LDC for the DARPA BOLT (Broad Operational Language Translation) program and consists of 388,027 words of Chinese and English parallel text enhanced with linguistic tags to indicate word relations. 

This release consists of Chinese source text message and chat conversations collected using two methods: new collection via LDC's collection platform, and donation of SMS and chat archives from BOLT collection participants. The source data is released as BOLT Chinese SMS/Chat (LDC2018T15).

The BOLT word alignment task was built on treebank annotation. LDC automatically extracted Chinese source tokens, including empty categories/traces, from word-segmented files provided by the BOLT Chinese Treebank annotation team at Brandeis University. The word-segmented tokens were then used to automatically generate ctb (Chinese Treebank) alignment, as well as tokenized for character alignment by inserting white spaces to separate characters.

BOLT Chinese-English Word Alignment and Tagging -- SMS/Chat Training is distributed via web download.

2019 Subscription Members will automatically receive copies of this corpus. 2019 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for $1750.

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(3) Machine Reading Phase 1 NFL Scoring Training Data was developed by LDC for use in the DARPA (Defense Advanced Research Projects Agency) Machine Reading program. It contains 110 U.S. NFL (National Football League) scoring source documents and 110 standoff annotation files, manually annotated for instances of NFL Scoring annotation categories defined with respect to a NFL Scoring ontology.

The Machine Reading program aimed to develop automated reading systems to bridge the gap between knowledge contained in natural language texts and knowledge accessible to formal reasoning systems. The reading systems designed by program participants were required to extract and reason about facts from text in multiple domains.

The data in this release constitutes the training data for the NFL Scoring Use Cases evaluation, which tested the sports domain by extracting information about scoring events and game outcomes and aligning that information with an NFL Scoring ontology.

Machine Reading Phase 1 NFL Scoring Training Data is distributed via web download.

2019 Subscription Members will automatically receive copies of this corpus. 2019 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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Membership Office

Linguistic Data Consortium

University of Pennsylvania

T: +1-215-573-1275

E: ldc@ldc.upenn.edu

M: 3600 Market St. Suite 810

      Philadelphia, PA 19104

 

 

 

 

 

 

 

 

 

 

 

 

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5-2-2ELRA - Language Resources Catalogue - Update (September 2019)
We are happy to announce that 1 new Bilingual Lexicon is now available in our catalogue.
ELRA-M0052 EnToFrNE - a Parallel English-French Lexicon of Named Entities
ISLRN: 233-270-965-120-8
This lexicon consists of 1,167,263 parallel named entities in English and French. The tags used are: PERSON, ORGANIZATION, LOCATION, PRODUCT and MISC. The lexicon comes in two formats: csv and xml.
For more information, see: http://catalog.elra.info/en-us/repository/browse/ELRA-M0052/

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

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

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







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5-2-3Speechocean – update (August 2019)

 

English Speech Recognition Corpus - Speechocean

 

At present, Speechocean has produced more than 24,000 hours of English Speech Recognition Corpora, including some rare corpora recorded by kids. Those corpora were recorded by 23,000 speakers in total. Please check the form below:

 

Name

Speakers

Hours

American English

8,441

8,029

Indian English

2,394

3,540

British English

2,381

3,029

Australian English

1,286

1,954

Chinese (Mainland) English

3,478

1,513

Canadian English

1,607

1,309

Japanese English

1,005

902

Singapore English

404

710

Russian English

230

492

Romanian English

201

389

French English

225

378

Chinese (Hong Kong) English

200

378

Italian English

213

366

Portugal English

201

341

Spainish English

200

326

German English

196

306

Korean English

116

207

Indonesian English

402

126

 

 

If you have any further inquiries, please do not hesitate to contact us.

Web: en.speechocean.com

Email: marketing@speechocean.com

 

 

 

 

 

 


 


 

 

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5-2-4Google '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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5-2-5Forensic database of voice recordings of 500+ Australian English speakers

Forensic database of voice recordings of 500+ Australian English speakers

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

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

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

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

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5-2-6Audio and Electroglottographic speech recordings

 

Audio and Electroglottographic speech recordings from several languages

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

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

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

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

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

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

Pat Keating (UCLA)

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5-2-7EEG-face tracking- audio 24 GB data set Kara One, Toronto, Canada

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

 

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

 

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

 

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

 

Best regards,

Frank

 

 

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

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

 

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5-2-8TORGO data base free for academic use.

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

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5-2-9Datatang

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.

 

Summary of the new datasets (2018) and a brief plan for 2019.

 

 

 

? Speech data (with annotation) that we finished in 2018 

 

Language
Datasets Length
  ( Hours )
French
794
British English
800
Spanish
435
Italian
1,440
German
1,800
Spanish (Mexico/Colombia)
700
Brazilian Portuguese
1,000
European Portuguese
1,000
Russian
1,000

 

?2019 ongoing  speech project 

 

Type

Project Name

Europeans speak English

1000 Hours-Spanish Speak English

1000 Hours-French Speak English

1000 Hours-German Speak English

Call Center Speech

1000 Hours-Call Center Speech

off-the-shelf data expansion

1000 Hours-Chinese Speak English

1500 Hours-Mixed Chinese and English Speech Data

 

 

 

On top of the above,  there are more planed speech data collections, such as Japanese speech data, children`s speech data, dialect speech data and so on.  

 

What is more, we will continually provide those data at a competitive price with a maintained high accuracy rate.

 

 

 

If you have any questions or need more details, do not hesitate to contact us jessy@datatang.com 

 

It would be possible to send you with a sample or specification of the data.

 

 

 


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5-2-10Fearless Steps Corpus (University of Texas, Dallas)

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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5-2-11SIWIS French Speech Synthesis Database
The SIWIS French Speech Synthesis Database includes high quality French speech recordings and associated text files, aimed at building TTS systems, investigate multiple styles, and emphasis. A total of 9750 utterances from various sources such as parliament debates and novels were uttered by a professional French voice talent. A subset of the database contains emphasised words in many different contexts. The database includes more than ten hours of speech data and is freely available.
 
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5-2-12JLCorpus - Emotional Speech corpus with primary and secondary emotions
JLCorpus - Emotional Speech corpus with primary and secondary emotions:
 

For further understanding the wide array of emotions embedded in human speech, we are introducing an emotional speech corpus. In contrast to the existing speech corpora, this corpus was constructed by maintaining an equal distribution of 4 long vowels in New Zealand English. This balance is to facilitate emotion related formant and glottal source feature comparison studies. Also, the corpus has 5 secondary emotions along with 5 primary emotions. Secondary emotions are important in Human-Robot Interaction (HRI), where the aim is to model natural conversations among humans and robots. But there are very few existing speech resources to study these emotions,and this work adds a speech corpus containing some secondary emotions.

Please use the corpus for emotional speech related studies. When you use it please include the citation as:

Jesin James, Li Tian, Catherine Watson, 'An Open Source Emotional Speech Corpus for Human Robot Interaction Applications', in Proc. Interspeech, 2018.

To access the whole corpus including the recording supporting files, click the following link: https://www.kaggle.com/tli725/jl-corpus, (if you have already installed the Kaggle API, you can type the following command to download: kaggle datasets download -d tli725/jl-corpus)

Or if you simply want the raw audio+txt files, click the following link: https://www.kaggle.com/tli725/jl-corpus/downloads/Raw%20JL%20corpus%20(unchecked%20and%20unannotated).rar/4

The corpus was evaluated by a large scale human perception test with 120 participants. The link to the survey are here- For Primary emorion corpus: https://auckland.au1.qualtrics.com/jfe/form/SV_8ewmOCgOFCHpAj3

For Secondary emotion corpus: https://auckland.au1.qualtrics.com/jfe/form/SV_eVDINp8WkKpsPsh

These surveys will give an overall idea about the type of recordings in the corpus.

The perceptually verified and annotated JL corpus will be given public access soon.

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5-2-13OPENGLOT –An open environment for the evaluation of glottal inverse filtering

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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5-2-14Corpus Rhapsodie

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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5-2-15The My Science Tutor Children?s Conversational Speech Corpus (MyST Corpus) , Boulder Learning Inc.

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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5-2-16HARVARD speech corpus - native British English speaker
  • HARVARD speech corpus - native British English speaker, digital re-recording
 
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