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ISCApad Archive  »  2019  »  ISCApad #250  »  Resources  »  Database

ISCApad #250

Friday, April 12, 2019 by Chris Wellekens

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

March 2019 Newsletter

 

 

In this newsletter:

 

Call for Papers – LTC 2019, LREC 2020

 

New Publications:

 

CALLFRIEND Egyptian Arabic Second Edition

 

Penn Discourse Treebank Version 3.0

 

 


Call for Papers

 

The 9th Language & Technology Conference (LTC 2019) will take place on May 17-19, 2019, at the Adam Mickiewicz University in Pozna?, Poland. LTC addresses Human Language Technologies as a challenge for computer science, linguistics, and related fields. Conference papers are due next week on Wednesday, March 20, 2019 (midnight, any time zone). For more information, visit the conference webpage.

 

The 12th Conference on Language Resources and Evaluation (LREC 2020) will take place on May 13-15, 2020, at the Palais du Pharo in Marseille, France. LREC aims to provide an overview of the state-of-the-art, explore new R&D directions and emerging trends, and exchange information regarding language resources and their applications, evaluation methodologies, and tools. Conference papers are due by November 25, 2019. For more information, including conference topics, visit the conference webpage.

 

 

 


New publications:

 

 

 

(1) CALLFRIEND Egyptian Arabic Second Edition was developed by LDC and consists of approximately 25 hours of unscripted telephone conversations between native speakers of Egyptian Arabic. 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 Egyptian Arabic (LDC96S49).

 

All data were 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 Egyptian Arabic 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 $1,000. 

 

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(2) Penn Discourse Treebank Version 3.0 is the third release in the Penn Discourse Treebank project, the goal of which is to annotate the Wall Street Journal (WSJ) section of Treebank-2 (LDC95T7) with discourse relations. Penn Discourse Treebank Version 2 (LDC2008T05) contains over 40,600 tokens of annotated relations. In Version 3, an additional 13,000 tokens were annotated, certain pairwise annotations were standardized, new senses were included, and the corpus was subject to a series of consistency checks.

 

This corpus contains two tools: (1) The Annotator, used for annotation and adjudication, and which can also be used for viewing the corpus; and (2) The Conversion Tool for converting Version 2 annotation files into the Version 3 format.

 

The documentation directory contains a manual describing what is new in Version 3 and how Version 3 differs from Version 2; the methods and guidelines used in annotating PDTB Version 3; and a range of statistics on the tokens, including the frequency of each connective, its sense labels, and its modifiers. More information about the corpus and research carried out by the developers and others using the corpus can be found on the PDTB website.

 

Penn Discourse Treebank Version 3.0 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 $1,000. 

 

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(3) VAST Chinese Speech and Transcripts was developed by LDC for the VAST (Video Annotation for Speech Technologies) project and is comprised of approximately 29 hours of Mandarin Chinese audio extracted from amateur video content harvested from the web and corresponding time-aligned transcripts.

 

Audio files were transcribed using XTrans, which supports manual transcription across multiple channels, languages, and platforms. Transcribers followed a Quick-Rich Transcription style; transcription guidelines are included in this release.

 

The aim of the VAST project was to collect and annotate data in several languages to support the development of speech technologies such as speech activity detection, language identification, speaker identification, and speech recognition.

 

VAST Chinese Speech and Transcripts 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 $1,000. 

 

 

 

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 (October 2018)
ELRA - Language Resources Catalogue - Update
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We are happy to announce that 2 new Written Corpora and 4 new Speech resources are now available in our catalogue.

ELRA-W0126 Training and test data for Arabizi detection and transliteration
ISLRN: 986-364-744-303-9
The dataset is composed of : a collection of mixed English and Arabizi text intended to train and test a system for the automatic detection of code-switching in mixed English and Arabizi texts ; and a set of 3,452 Arabizi tokens manually transliterated into Arabic, intended to train and test a system that performs Arabizi to Arabic transliteration.
For more information, see: http://catalog.elra.info/en-us/repository/browse/ELRA-W0126/

ELRA-W0127 Normalized Arabic Fragments for Inestimable Stemming (NAFIS)
ISLRN: 305-450-745-774-1
This is an Arabic stemming gold standard corpus composed by a collection of 37 sentences, selected to be representative of Arabic stemming tasks and manually annotated. Compiled sentences belong to various sources (poems, holy Quran, books, and periodics) of diversified kinds (proverb and dictum, article commentary, religious text, literature, historical fiction). NAFIS is represented according to the TEI standard.   
For more information, see: http://catalog.elra.info/en-us/repository/browse/ELRA-W0127/

ELRA-S0396 Mbochi speech corpus

ISLRN: 747-055-093-447-8
This corpus consists of 5131 sentences recorded in Mbochi, together with their transcription and French translation, as well as the results from the work made during  JSALT workshop: alignments at the phonetic level and various results of unsupervised word segmentation from audio. The audio corpus is made up of 4,5 hours, downsampled at 16kHz, 16bits, with Linear PCM encoding. Data is distributed into 2 parts, one for training consisting of 4617 sentences, and one for development consisting of 514 sentences.
For more information, see: http://catalog.elra.info/en-us/repository/browse/ELRA-S0396/

ELRA-S0397 Chinese Mandarin (South) database

ISLRN: 503-886-852-083-2
This database contains the recordings of 1000 Chinese Mandarin speakers from Southern China (500 males and 500 females), from 18 to 60 years? old, recorded in quiet studios. Recordings were made through microphone headsets and consist of 341 hours of audio data (about 30 minutes per speaker), stored in .WAV files as sequences of 48 KHz Mono, 16 bits, Linear PCM.
For more information, see: http://catalog.elra.info/en-us/repository/browse/ELRA-S0397/

ELRA-S0398 Chinese Mandarin (North) database
ISLRN: 353-548-770-894-7
This database contains the recordings of 500 Chinese Mandarin speakers from Northern China (250 males and 250 females), from 18 to 60 years? old, recorded in quiet studios. Recordings were made through microphone headsets and consist of 172 hours of audio data (about 30 minutes per speaker), stored in .WAV files as sequences of 48 KHz Mono, 16 bits, Linear PCM.
For more information, see: http://catalog.elra.info/en-us/repository/browse/ELRA-S0398/

ELRA-S0401 Persian Audio Dictionary
ISLRN: 133-181-128-420-9
This dictionary consists of more than 50,000 entries (along with almost all wordforms and proper names) with corresponding audio files in MP3 and English transliterations. The words have been recorded with standard Persian (Farsi) pronunciation (all by a single speaker). This dictionary is provided with its software.
For more information, see: http://catalog.elra.info/en-us/repository/browse/ELRA-S0401/

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 (April 2019)

 

Cantonese Speech Recognition Corpus --- Speechocean

 

Speechocean: A.I. Data Resource & Service Supplier

 

At present, we are capable to provide around 8000 hours Cantonese speech recognition corpus, including Mainland Cantonese and Hong Kong Cantonese. Please check the form below: http://kingline.speechocean.com

 

Language

Content

Speakers

Hours

Mainland Cantonese

Sentences

4,590

5,220

Mainland Cantonese

Conversation

450

390

Hong Kong Cantonese

Sentences

960

670

Hong Kong Cantonese

Conversation

770

1,580

 


 More Information

  • Information of Speaker: Selected native speakers. Balanced covering ages, gender and regional accents.

  • Recording Environment: Quiet or noisy environment.

  • Recording Platform: Desktop, mobile or telephone

  • Post Processing: Proofreading, transcription, annotation and quality control.

  • Lexicon: Included

 

 

 

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

Web: http://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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