ISCA - International Speech
Communication Association


ISCApad Archive  »  2020  »  ISCApad #264  »  Resources  »  Database

ISCApad #264

Wednesday, June 10, 2020 by Chris Wellekens

5-2 Database
5-2-1Linguistic Data Consortium (LDC) update (May 2020)

 

 

In this newsletter:

New Publications:
LORELEI Oromo Incident Language Pack
LORELEI Entity Detection and Linking Knowledge Base
BOLT English Translation Treebank - Chinese Discussion Forum
Multi-Language Conversational Telephone Speech 2011 -- Mandarin Chinese


 


 

New publications:

(1) LORELEI Oromo Incident Language Pack was developed by LDC and is comprised of approximately 3.9 million words of Oromo monolingual text, 25,000 words of English monolingual text, 135,000 words of parallel and comparable Oromo-English text, and 50,000 words of data annotated for Entity Discovery and Linking and for Situation Frames. It contains all of the text data, annotations, supplemental resources, and related software tools for the Oromo language that were used in the DARPA LORELEI / LoReHLT 2017 Evaluation.

The evaluation protocol was based on a scenario in which an unforeseen event triggered a need for humanitarian and logistical support in a region where the incident language had received little or no attention in NLP research. Evaluation participants provided NLP solutions, including information extraction and machine translation, with limited resources and limited development time. 


Data was collected from news, social network, weblog, newsgroup, discussion forum, and reference material. Entity Detection and Linking and Situation Frame annotations identified “entities,” “needs” (such as a need for food), and “issues” (such as civil unrest) to be detected by systems for scoring purposes. Situation frame analysis was designed to extract basic information that would be useful for planning a disaster response effort.

The knowledge base for the entity linking annotation in this corpus is available separately as LORELEI Entity Detection and Linking Knowledge Base (LDC2020T10).

LORELEI Oromo Incident 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 $250.

 

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(2) LORELEI Entity Detection and Linking Knowledge Base was developed by LDC and contains the full LORELEI Entity Detection and Linking (EDL) Knowledge Base (KB) used for all LORELEI Representative Language and Incident Language Pack entity linking annotation. 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.

 

 

 

The KB in this release supported the EDL task in LORELEI for four entity types -- geo-political entities (GPE), locations (LOC), persons (PER), and organizations (ORG) -- and contains a total of 10,216,832 entities. There are four inputs to the KB, each designated by a unique 'origin' code in the KB, as follows: GPE and LOC entities from a snapshot of GeoNames, PER entities from the CIA World Leaders List, ORG entities from Appendix B of the CIA World Factbook, and additional entities manually created by LDC for each of the representative and incident languages in the LORELEI Program.

LORELEI Entity Detection and Linking Knowledge Base 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 $250.

 

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(3) BOLT English Translation Treebank - Chinese Discussion Forum was developed by LDC and consists of 147,432 tokens of web discussion forum data translated from Chinese to English and annotated for part-of-speech and syntactic structure.

 

 

 

The source data is Chinese discussion forum web text collected by LDC in 2011 and 2012, translated into English and released in BOLT Chinese Discussion Forum Parallel Training Data (LDC2017T05). A subset of the translated text -- 148 files representing 147,432 tokens -- was selected for the treebank and annotated for word-level tokenization, part-of-speech, and syntactic structure. Only the translated English text is included in the source data for this release.

 

 

 

Part-of-speech and treebank annotation conformed to Penn Treebank II style, incorporating changes to those guidelines that were developed under the GALE (Global Autonomous Language Exploitation) program. Supplementary guidelines for English treebanks and web text are included with this release.

 

 

 

BOLT English Translation Treebank - Chinese Discussion Forum 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 $1750.

 

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(4) Multi-Language Conversational Telephone Speech 2011 -- Mandarin Chinese was developed by LDC and is comprised of approximately 25 hours of telephone speech in Mandarin Chinese.

 

 

 

The data were collected primarily to support research and technology evaluation in automatic language identification, and portions of these telephone calls were used in the NIST 2011 Language Recognition Evaluation (LRE). Participants were recruited by native speakers who contacted acquaintances in their social network. Those native speakers made one call, up to 15 minutes, to each acquaintance. The data was collected using LDC's telephone collection infrastructure, comprised of three computer telephony systems. Human auditors labeled calls for callee gender, dialect type, and noise.

 

 

 

LDC has also released the following as part of the Multi-Language Conversational Telephone Speech 2011 series:

 

 

Multi-Language Conversational Telephone Speech 2011 -- Mandarin Chinese 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 $1500.

 

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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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5-2-2ELRA - Language Resources Catalogue - Update (May 2020)
We are happy to announce that 1 new Speech resource is now available in our catalogue.
 
Mandarin Chinese Conversational Recognition Corpus from Magic Data Tech
This dataset consists of 4.98 hours of transcribed conversational speech in Mandarin Chinese, where 30 conversations are uttered by 32 speakers (16 males and 16 females). The audios are sampled at 16 kHz and quantized at 16 bits.
For each conversation, there are two close-talking channels recorded via the microphones, one for each speaker, as well as three far-field channels recorded by iPhone, Androïd Phone, and recorder respectively.

This corpus may be obtained as a complete set or by selecting specific channels (two close-talking channels shall be understood as 1 single channel):

ELRA-S0409-01 MDT Mandarin Chinese Conversational Recognition Corpus - complete set
ISLRN: 559-956-475-937-1
For more information, see: http://catalog.elra.info/en-us/repository/browse/ELRA-S0409_01
ELRA-S0409-02 MDT Mandarin Chinese Conversational Recognition Corpus - 1 channel
ISLRN: 234-140-315-272-4
For more information, see: http://catalog.elra.info/en-us/repository/browse/ELRA-S0409_02
ELRA-S0409-03 MDT Mandarin Chinese Conversational Recognition Corpus - 2 channels
ISLRN: 383-054-806-637-3
For more information, see: http://catalog.elra.info/en-us/repository/browse/ELRA-S0409_03
ELRA-S0409-04 MDT Mandarin Chinese Conversational Recognition Corpus - 3 channels
ISLRN: 235-882-638-211-2
For more information, see: http://catalog.elra.info/en-us/repository/browse/ELRA-S0409_04

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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5-2-17Magic Data Technology Kid Voice TTS Corpus in Mandarin Chinese (November 2019)

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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5-2-18FlauBERT: a French LM
Here is FlauBERT: a French LM learnt (with #CNRS J-Zay supercomputer) on a large and heterogeneous corpus. Along with it comes FLUE (evaluation setup for French NLP). FlauBERT was successfully applied to complex tasks (NLI, WSD, Parsing).  More on https://github.com/getalp/Flaubert
More details on this online paper: https://arxiv.org/abs/1912.05372 
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5-2-19ELRA-S0408 Speechtera Pronunciation Dictionary

ELRA-S0408 Speechtera Pronunciation Dictionary

ISLRN: 645-563-102-594-8
The SpeechTera Pronunciation Dictionary is a machine-readable pronunciation dictionary for Brazilian Portuguese and comprises 737,347 entries. Its phonetic transcription is based on 13 linguistics varieties spoken in Brazil and contains the pronunciation of the frequent word forms found in the transcription data of the SpeechTera's speech and text database (literary, newspaper, movies, miscellaneous). Each one of the thirteen dialects comprises 56,719 entries.
For more information, see: http://catalog.elra.info/en-us/repository/browse/ELRA-S0408/

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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5-2-20Ressources of ELRC Network

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.

*****
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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5-2-21Language Resources distribution agreement between ELRA and SpeechOcean

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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5-2-22Sharing Language Ressourses via ELRA

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:

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