In this newsletter:
30th Anniversary Highlight: Penn Treebank

New publications:
NUBUC
Samrómur Icelandic Speech 1.0

30th Anniversary Highlight: Penn Treebank
LDC’s Catalog features classic corpora responsible for critical advances in human language technology that continue to influence researchers. Among them are the Penn Treebank releases, Treebank-2 (LDC96T7) and Treebank-3 (LDC99T42).

The Penn Treebank project (1989-1996) produced seven million words tagged for part-of-speech, three million words of parsed text, over two million words annotated for predicate-argument structure and 1.6 million words of transcribed speech annotated for speech disfluencies (Taylor et al., 2003). Source material represents a diverse range of data, including Wall Street Journal (WSJ) articles, the Brown Corpus and Switchboard telephone conversations.

Penn Treebanks are used for a wide range of purposes, including the creation and training of parsers and taggers, work on machine translation and speech recognition, and research concerning joint syntactic and semantic role labeling. Their ongoing influence is evidenced by the popularity of Treebank-3 (LDC99T42), which continues to be one of LDC’s top ten most distributed corpora in the Catalog. In addition, the WSJ section has served as a model for treebanks across many languages (Nivre, 2008).

The Penn Treebank has inspired related annotation schemes, such as Proposition Bank, the Penn Discourse Treebank project, and word alignment annotation. In addition, LDC has developed revised English treebank guidelines resulting in the re-issue of the WSJ section (English News Text Treebank: Penn Treebank Revised (LDC2015T13)) and treebanked web text (e.g., English Web Treebank (LDC2012T13) and BOLT English Translation Treebank – Chinese Discussion Forum (LDC2020T09)).  

Penn Treebank corpora and its related releases are available for licensing to LDC members and nonmembers. For more information about licensing LDC data, visit Obtaining Data.

New publications:
(1)  NUBUC (NyU-BU contextually controlled stories Corpus) was developed by New York University, Max Planck Institute for Empirical Aesthetics and Boston University. It contains approximately three hours of English read speech from eight stories focused on linguistic keywords that were created specifically for this corpus, along with transcripts, syntactic annotations, and corpus metadata.

Stories are centered on a protagonist and bear a similarity to a modern fairy tale. Each story consists of approximately 2,000 words organized around critical keywords matched along multiple linguistic dimensions. The story texts comprise a total of 1024 sentences and 16,472 words. Each story was read by two different voice actors, one male and one female, in a neutral American English accent.

Recordings are 11-12 minutes in duration, for a total of about 90 minutes of continuous speech per speaker.

NUBUC is distributed via web download.  

2022 Subscription Members will automatically receive copies of this corpus. 2022 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data at no cost.

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(2) Samrómur Icelandic Speech 1.0 was developed by the Language and Voice Lab, Reykjavik University in cooperation with Almannarómur, Center for Language Technology. The corpus contains 145 hours of Icelandic prompted speech from 8,392 speakers representing 100,000 utterances.

Speech data was collected between October 2019 and May 2021 using the Samrómur website which displayed prompts to participants. The prompts were mainly from The Icelandic Gigaword Corpus, which includes text from novels, news, plays, and from a list of location names in Iceland. Additional prompts were taken from the Icelandic Web of Science and others were created by combining a name followed by a question or a demand. Prompts and speaker metadata are included in the corpus.

Samrómur Icelandic Speech 1.0 is distributed via web download.  

2022 Subscription Members will automatically receive copies of this corpus provided they have submitted a completed copy of the special license agreement. 2022 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for $250.

To unsubscribe from this newsletter, log in to your LDC account and uncheck the box next to “Receive Newsletter” under Account Options; or contact LDC for assistance.

Membership Coordinator

Linguistic Data Consortium

University of Pennsylvania

T: +1-215-573-1275

E: ldc@ldc.upenn.edu

M: 3600 Market St. Suite 810

      Philadelphia, PA 19104

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Forensic database of voice recordings of 500+ Australian English speakers

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

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

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

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

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Audio and Electroglottographic speech recordings from several languages

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

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

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

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

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

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

Pat Keating (UCLA)

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

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

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

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

Best regards,

Frank

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

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

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

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

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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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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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Out of the 7,000+ language spoken around the world, only a few have associated Language Technologies. The majority of languages can be considered as 'under-resourced' or as 'not supported'. This situation, very detrimental to many languages speakers, and specifically indigenous languages speakers, creates a digital divide,  and places many languages in danger of digital extinction, if not complete extinction.

Organized as part of the 2019 International Year of Indigenous Languages, the 1st edition of LT4All (Language Technologies for All: Enabling Linguistic Diversity and Multilingualism Worldwide) took place in Paris at the UNESCO Headquarters on December 4-6, 2019 and gathered 400 participants from various backgrounds (including language science and technology researchers, linguists, industrials, indigenous peoples, language policy and decision makers) from all over the world.

The LT4All Programme and Editorial Committees are very happy to announce that the set of Research Papers and Posters collected at the occasion of LT4All is now available online at : https://lt4all.elra.info/proceedings/lt4all2019/

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LT4All has  been made possible thanks to the close cooperation between UNESCO, the  Government of the Khanty-Mansiysk Autonomous Okrug-Ugra (Russian Federation), the European Language Resources Association (ELRA) and its Special Interest  Group on Under-resourced  languages  (SIGUL), and in partnership with UNESCO Intergovernmental Information for All Programme (IFAP) and the Interregional Library Cooperation Centre, as well as with support of other public organizations and sponsors.

More information including the list of all the sponsors and supporters @ https://en.unesco.org/LT4All

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Search and Find ELRA LRs on Google Dataset Search and ELG LT Platform

ELRA is happy to announce that all the Language Resources from its Catalogue can now be searched and found on Google Dataset Search and on the ELG Language Technology platform developed within the European Language Grid project.

In order to allow the indexing by Google Dataset Search, ELRA has updated the code generating the catalogue pages. The code developed follows the schema.org standard and is publicly available in JSON format so that it can be used for other harvesting purposes.

The ELRA Catalogue is already indexed and harvested by famous repositories and archives such as OLAC (Open Language Archives Community), CLARIN Virtual Language Observatory and META-SHARE.

For 25 years now, ELRA has been distributing Language Resources to support research and development in various fields of Human Language Technology. The indexing on both Google Dataset Search and the ELG LT Plaform is increasing ELRA Catalogue?s visibility, making the LRs known to new visitors from the Human Language Technologies, Artificial Intelligence and other related fields.

*** 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).

ELRA Catalogue of Language Resources: http://catalogue.elra.info

More about ELRA, please visit: http://www.elra.info.

*** About Google Dataset Search ***

Google Dataset Search is a search engine for datasets that enables users to search through a list of data repositories indexed through a standardised schema.

More about Google Dataset Search: https://datasetsearch.research.google.com/

*** About European Language Grid ***

The European Language Grid (ELG) is a project funded by the European Union through the Horizon 2020 research and innovation programme. It aims to be a primary platform for Language Technology in Europe.

More about the European Language Grid project: https://www.european-language-grid.eu/

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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.

Despite the cancellation of LREC 2020 in Marseille, a high number of contributions was submitted and the LREC initiative 'Share your LRs' could be conducted to the end successfully.

Repositories corresponding to each edition of the conference are available here:

• 179 LRs shared in 2020 are available at https://bit.ly/3o836kM
• 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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With NSF support, our interdisciplinary team of voice research at UCLA recently put together a public database that we believe will be of interest to many members of the ISCA community. On behalf of my co-authors (Patricia Keating, Jody Kreiman, Abeer Alwan, Adam Chong), I'm writing to ask if we could advertise our database in the ISCA newsletter. We'd really appreciate your help with this.

The UCLA Variability Speaker Database comprises high-quality audio recordings from 202 speakers, 101 men 

and 101 women, performing 12 brief speech tasks in English over three recording sessions (total amount 

of speech: 300-450 sec per speaker). This public database was designed to sample variability in speaking 

within individual speakers and across a large number of speakers. The large set of speakers (similar in age) 

sampled from the current university community is gender-balanced and has a variety of language backgrounds. 

The database can serve as a testing ground for research questions involving between-speaker variability, 

within-speaker variability, and text-dependent variability. 

More details about the database are available in a readme file that can be sent on request.

--Cynthia Yoonjeong Lee

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We are pleased to announce that Language Resources entrusted to ELRA for distribution and shared by the Universitat Politecnica de Catalunya (UPC), in Spain, are now available for free for academic research purposes (for ELRA institutional members) and at substantially decreased costs for commercial purposes. All data have been developed to enhance Speech technologies in Catalan, Spanish and Arabic.

The Language Resources can be found in the ELRA Catalogue under the following references:

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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A USC Multispeaker speech production articulatory datasets of vocal tract MRI video
 the 'USC 75-Speaker Speech MRI Database'  is a new freely-available speech production data set with accompanying software  tools:
https://www.nature.com/articles/s41597-021-00976-x

These data contain 2D sagittal-view RT-MRI videos along with synchronized  audio for 75 subjects performing linguistically motivated speech tasks,  alongside the corresponding raw RT-MRI data. The dataset also includes
3D volumetric vocal tract MRI during sustained speech sounds and  high-resolution static anatomical T2-weighted upper airway MRI for each  subject. 

Other speech production datasets of articulatory data that are also freely available  include  a TIMIT articulatory data corpus and emotional speech production data, all available from:  https://sail.usc.edu/span/resources.html

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