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ISCApad #293 |
| Tuesday, November 08, 2022 by Chris Wellekens |
5 Resources
| 5-1-1 | Benjamin Weiss, 'Talker Quality in Human and Machine Interaction - Modeling the Listener’s Perspective in Passive and Interactive Scenarios'. T-Labs Series in Telecommunication Services. Springer Nature, Cham. (2020) Benjamin Weiss (2020): 'Talker Quality in Human and Machine Interaction - Modeling the Listener’s Perspective in Passive and Interactive Scenarios'. T-Labs Series in Telecommunication Services. Springer Nature, Cham.
https://rd.springer.com/book/10.1007/978-3-030-22769-2
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| 5-1-2 | W.F.Katz, P.F.Assman, 'The Routledge Handbook of Phonetics', Routledge.
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| 5-1-3 | Proceedings of SLTU-CCURL2020 Dear all, we are very happy to announce that the SLTU-CCURL2020 Proceedings are available online: https://lrec2020.lrec-conf.org/media/proceedings/Workshops/Books/SLTUCCURLbook.pdf
This year, LREC2020 would have featured an extraordinary event: the first joint SLTU-CCURL2020 Workshop, which was planned as a two-day workshop, with 54 papers accepted either as oral and poster presentations.
The workshop program was enriched by two tutorials and two keynote speeches.
We will miss the presentations, the discussions and the overall stimulating environment very deeply.
We are thankful to ELRA and ISCA for their support to the workshop, to our Google sponsor and to the 60 experts of the Program Committee, who worked tirelessly in order to help us to select the best papers representing a wide perspective over NLP, speech and computational linguistics addressing less-resource languages.
Looking forward to better times when we will be able to meet in person again, we hope that you will find these workshop proceedings relevant and stimulating for your own research.
With our best wishes,
Claudia Soria, Laurent Besacier, Dorothee Beermann, and Sakriani Sakti
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| 5-1-4 | J.Blauert, J. Braasch, 'The Technology of Binaural Understanding', Springer and ASA-Press My name is Jens Blauert, and you may recall me as an ESCA-Founder and ISCA-Goldmedalist. Although I am professor emeritus since many years, I am still active in science.
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| 5-1-5 | Weiss B., Trouvain J., Barkat-Defradas M., Ohala J.J., 'Voice Attractiveness', Springer 2021Voice AttractivenessVoice attractivenessStudies on Sexy, Likable, and Charismatic Speakers
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| 5-1-6 | Proceedings Speech Prosody 2022 Dear Speech Prosody SIG Members,
As many of you already know, Speech Prosody 2022 was a great technical and social success! Our thanks to Sonia Frota, Marina Vigario, and all the organizers.
The proceedings are already available, at https://www.isca-speech.org/archive/speechprosody_2022/ .
Also, to share a link announced at the closing ceremony, there are now digitized, searchable versions of all past ICPhS proceedings, at https://www.coli.uni-saarland.de/groups/BM/phonetics/resources.html#icphs .
Nigel Ward, SProSIG Chair, Professor of Computer Science, University of Texas at El Paso nigel@utep.edu https://www.cs.utep.edu/nigel/
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| 5-1-7 | Diana Sidtis, Foundations of Familiar Language, Wiley -----
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| 5-2-1 | Linguistic Data Consortium (LDC) update (October 2022)
In this newsletter: Membership Year 2023 publication preview
Check your inbox in the coming weeks for more information about membership renewal. New publications: * 2017 NIST Language Recognition Evaluation Training and Development Sets contains training and development material for the 2017 NIST Language Recognition Evaluation. It consists of 2,100 hours of conversational telephone speech, broadcast conversation, broadcast narrow band speech, and speech from video in the following 14 languages, dialects, and varieties: Arabic (Iraqi, Levantine, Maghrebi, Egyptian), English (British, American), Polish, Russian, Portuguese (Brazilian), Spanish (Caribbean, European, Latin American Continental), and Chinese (Mandarin, Min Nan). The 2017 evaluation focused on differentiating closely related language pairs. Source data is from LDC's CALLFRIEND and Fisher telephone collections, the VAST video collection, various broadcast sources, and earlier NIST LRE test sets.
2022 members can access this corpus through their LDC accounts. Non-members may license this data for $1500. * LORELEI Bengali Representative Language Pack was developed by LDC and is comprised of approximately 144 million words of Bengali monolingual text, 96,000 Bengali words translated from English data, and over 2 million words of found Bengali-English parallel text. Approximately 86,000 words were annotated for named entities and up to 25,000 words were annotated for entity discovery and linking and situation frames (identifying entities, needs and issues). Data was collected from news, social network, and weblogs. Membership Coordinator 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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| 5-2-2 | ELRA - Language Resources Catalogue - Update (October 2022) We are happy to announce that 6 new written corpora, 1 new monolingual lexicon and 1 new speech resource and 1 new multimodal resource are now available in our catalogue.
ISLRN: 252-495-813-736-1 The AnCora Spanish Corpus 2.0.0 is a corpus of 500,000 words annotated at different levels: Lemma and Part of Speech, Syntactic constituents and functions, Argument structure and thematic roles, Semantic classes of the verb, Denotative type of deverbal nouns, Nouns related to WordNet synsets, Named Entities, Coreference relation.
AnCora Catalan 2.0.0
Bulgarian Treebank Corpus
Bulgarian Event Corpus
Bulgarian Valency Frame Lexicon
How2Sign Dataset
Persian Speech Corpus
Venice Italian Treebank (VIT) – version 2 Wojood - A corpus for nested Arabic Named Entity Recognition
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| 5-2-3 | Speechocean – update (August 2019)
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| 5-2-4 | Google 's Language Model benchmark A LM benchmark is available at:https://github.com/ciprian-chelba/1-billion-word-language-modeling-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:
ArXiv paper: http://arxiv.org/abs/1312.3005
Happy benchmarking!'
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| 5-2-5 | Forensic database of voice recordings of 500+ Australian English speakers Forensic database of voice recordings of 500+ Australian English speakers
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| 5-2-6 | Audio 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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| 5-2-7 | EEG-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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| 5-2-8 | TORGO 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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| 5-2-9 | Datatang 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
?2019 ongoing speech project
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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| 5-2-10 | SIWIS 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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| 5-2-11 | JLCorpus - 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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| 5-2-12 | OPENGLOT –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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| 5-2-13 | Corpus Rhapsodie Nous sommes heureux de vous annoncer la publication d¹un ouvrage consacré
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| 5-2-14 | The 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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| 5-2-15 | HARVARD speech corpus - native British English speaker
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| 5-2-16 | Magic 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 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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| 5-2-17 | FlauBERT: 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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| 5-2-18 | ELRA-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
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| 5-2-19 | Ressources 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. For more information on the catalogue, please contact Valérie Mapelli
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| 5-2-20 | ELRA announces that MEDIA data are now available for free for academic research 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: 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 *** 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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| 5-2-21 | ELRA/ELDA Communication : LT4all 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.
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| 5-2-22 | Search and Find ELRA LRs on Google Dataset Search and ELG LT Platform 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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| 5-2-23 | Sharing language resources (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. 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:
For more info and questions, please write to contact@elda.org.
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| 5-2-24 | The UCLA Variability Speaker Database 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 database, the UCLA Variability Speaker Database, is freely available through UCLA's Box cloud, which can be accessed from our lab website: http://www.seas.ucla.edu/spapl/shareware.html#Data I should mention that the database will also be available from the Linguistic Data Consortium (LDC) as of October, 2021.
Here's a brief description of the database.
Postdoctoral Scholar, Department of Linguistics, UCLA
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| 5-2-25 | Free databases in Catalan, Spanish and Arabic (ELRA and UPC Spain) 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: ELRA-S0101 Spanish SpeechDat(II) FDB-1000 (ISLRN: 415-072-153-167-5)
For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0101/ ELRA-S0102 Spanish SpeechDat(II) FDB-4000 (ISLRN: 295-399-069-106-4) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0102/ ELRA-S0140 Spanish SpeechDat-Car database (ISLRN: 937-459-364-430-3) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0140/ ELRA-S0141 SALA Spanish Venezuelan Database (ISLRN: 894-744-522-508-8) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0141/ ELRA-S0173 SALA Spanish Mexican Database (ISLRN: 077-043-759-782-3) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0173/ ELRA-S0183 OrienTel Morocco MCA (Modern Colloquial Arabic) database (ISLRN: 613-578-868-832-2) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0183/ ELRA-S0184 OrienTel Morocco MSA (Modern Standard Arabic) database (ISLRN: 978-839-138-181-8) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0184/ ELRA-S0185 OrienTel French as spoken in Morocco database (ISLRN: 299-422-451-969-8) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0185/ ELRA-S0186 OrienTel Tunisia MCA (Modern Colloquial Arabic) database (ISLRN: 297-705-745-294-4) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0186/ ELRA-S0187 OrienTel Tunisia MSA (Modern Standard Arabic) database (ISLRN: 926-401-827-806-5) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0187/ ELRA-S0188 OrienTel French as spoken in Tunisia database (ISLRN: 085-972-271-578-3) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0188/ ELRA-S0207 LC-STAR Catalan phonetic lexicon (ISLRN: 102-856-174-704-7) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0207/ ELRA-S0208 LC-STAR Spanish phonetic lexicon (ISLRN: 826-939-678-247-5) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0208/ ELRA-S0243 SpeechDat Catalan FDB database (ISLRN: 373-541-490-506-3) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0243/ ELRA-S0306 TC-STAR Transcriptions of Spanish Parliamentary Speech (ISLRN: 972-398-693-247-4 ) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0306/ ELRA-S0309 TC-STAR Spanish Baseline Female Speech Database (ISLRN: 682-113-241-701-0) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0309/ ELRA-S0310 TC-STAR Spanish Baseline Male Speech Database (ISLRN: 736-021-086-598-0) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0310/ ELRA-S0311 TC-STAR Bilingual Voice-Conversion Spanish Speech Database (ISLRN: 254-311-004-570-0) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0311/ ELRA-S0312 TC-STAR Bilingual Voice-Conversion English Speech Database (ISLRN: 522-613-023-181-1) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0312/ ELRA-S0313 TC-STAR Bilingual Expressive Speech Database (ISLRN: 088-656-828-489-3) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0313/ ELRA-S0336 Spanish Festival voice male (ISLRN: 868-352-143-949-9) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0336/ ELRA-S0337 Spanish Festival voice female (ISLRN: 396-262-481-019-0) For more information, see: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0337/ 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
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| 5-2-26 | USC 75-Speaker Speech MRI Database. Multispeaker speech production articulatory datasets of vocal tract MRI video A USC Multispeaker speech production articulatory datasets of vocal tract MRI video 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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| 5-2-27 | LR Agreement betweel ELRA and Datatang Paris, France, October 24, 2022/
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| 5-3-1 | Cantor Digitalis, an open-source real-time singing synthesizer controlled by hand gestures. We are glad to announce the public realease of the Cantor Digitalis, an open-source real-time singing synthesizer controlled by hand gestures. It can be used e.g. for making music or for singing voice pedagogy. A wide variety of voices are available, from the classic vocal quartet (soprano, alto, tenor, bass), to the extreme colors of childish, breathy, roaring, etc. voices. All the features of vocal sounds are entirely under control, as the synthesis method is based on a mathematic model of voice production, without prerecording segments. The instrument is controlled using chironomy, i.e. hand gestures, with the help of interfaces like stylus or fingers on a graphic tablet, or computer mouse. Vocal dimensions such as the melody, vocal effort, vowel, voice tension, vocal tract size, breathiness etc. can easily and continuously be controlled during performance, and special voices can be prepared in advance or using presets. Check out the capabilities of Cantor Digitalis, through performances extracts from the ensemble Chorus Digitalis: http://youtu.be/_LTjM3Lihis?t=13s. In pratice, this release provides:
Regards,
The Cantor Digitalis team (who loves feedback — cantordigitalis@limsi.fr) Christophe d'Alessandro, Lionel Feugère, Olivier Perrotin http://cantordigitalis.limsi.fr/
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| 5-3-2 | MultiVec: a Multilingual and MultiLevel Representation Learning Toolkit for NLP
We are happy to announce the release of our new toolkit “MultiVec” for computing continuous representations for text at different granularity levels (word-level or sequences of words). MultiVec includes Mikolov et al. [2013b]’s word2vec features, Le and Mikolov [2014]’s paragraph vector (batch and online) and Luong et al. [2015]’s model for bilingual distributed representations. MultiVec also includes different distance measures between words and sequences of words. The toolkit is written in C++ and is aimed at being fast (in the same order of magnitude as word2vec), easy to use, and easy to extend. It has been evaluated on several NLP tasks: the analogical reasoning task, sentiment analysis, and crosslingual document classification. The toolkit also includes C++ and Python libraries, that you can use to query bilingual and monolingual models.
The project is fully open to future contributions. The code is provided on the project webpage (https://github.com/eske/multivec) with installation instructions and command-line usage examples.
When you use this toolkit, please cite:
@InProceedings{MultiVecLREC2016, Title = {{MultiVec: a Multilingual and MultiLevel Representation Learning Toolkit for NLP}}, Author = {Alexandre Bérard and Christophe Servan and Olivier Pietquin and Laurent Besacier}, Booktitle = {The 10th edition of the Language Resources and Evaluation Conference (LREC 2016)}, Year = {2016}, Month = {May} }
The paper is available here: https://github.com/eske/multivec/raw/master/docs/Berard_and_al-MultiVec_a_Multilingual_and_Multilevel_Representation_Learning_Toolkit_for_NLP-LREC2016.pdf
Best regards,
Alexandre Bérard, Christophe Servan, Olivier Pietquin and Laurent Besacier
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| 5-3-3 | An android application for speech data collection LIG_AIKUMA We are pleased to announce the release of LIG_AIKUMA, an android application for speech data collection, specially dedicated to language documentation. LIG_AIKUMA is an improved version of the Android application (AIKUMA) initially developed by Steven Bird and colleagues. Features were added to the app in order to facilitate the collection of parallel speech data in line with the requirements of a French-German project (ANR/DFG BULB - Breaking the Unwritten Language Barrier).
The resulting app, called LIG-AIKUMA, runs on various mobile phones and tablets and proposes a range of different speech collection modes (recording, respeaking, translation and elicitation). It was used for field data collections in Congo-Brazzaville resulting in a total of over 80 hours of speech.
Users who just want to use the app without access to the code can download it directly from the forge direct link: https://forge.imag.fr/frs/download.php/706/MainActivity.apk
Code is also available on demand (contact elodie.gauthier@imag.fr and laurent.besacier@imag.fr).
More details on LIG_AIKUMA can be found on the following paper: http://www.sciencedirect.com/science/article/pii/S1877050916300448
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| 5-3-4 | Web services via ALL GO from IRISA-CNRS It is our pleasure to introduce A||GO (https://allgo.inria.fr/ or http://allgo.irisa.fr/), a platform providing a collection of web-services for the automatic analysis of various data, including multimedia content across modalities. The platform builds on the back-end web service deployment infrastructure developed and maintained by Inria?s Service for Experimentation and Development (SED). Originally dedicated to multimedia content, A||GO progressively broadened to other fields such as computational biology, networks and telecommunications, computational graphics or computational physics.
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| 5-3-5 | Clickable map - Illustrations of the IPA Clickable map - Illustrations of the IPA
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| 5-3-6 | LIG-Aikuma running on mobile phones and tablets
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| 5-3-7 | Python Library Nous sommes heureux d'annoncer la mise à disposition du public de la
première bibliothèque en langage Python pour convertir des nombres écrits en
français en leur représentation en chiffres.
L'analyseur est robuste et est capable de segmenter et substituer les expressions
de nombre dans un flux de mots, comme une conversation par exemple. Il reconnaît les différentes
variantes de la langue (quantre-vingt-dix / nonante?) et traduit aussi bien les
ordinaux que les entiers, les nombres décimaux et les séquences formelles (n° de téléphone, CB?).
Nous espérons que cet outil sera utile à celles et ceux qui, comme nous, font du traitment
du langage naturel en français.
Cette bibliothèque est diffusée sous license MIT qui permet une utilisation très libre.
Sources : https://github.com/allo-media/text2num
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| 5-3-8 | Evaluation des troubles moteurs de la parole MONPAGE version 2.0.s Chères et chers collègues,
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| 5-3-9 | VocalTractLab3D: articulatory synthesis software. Bonjour à tous,
Je vous informe par ce mail que le logiciel de synthèse articulatoire VocalTractLab3D est maintenant en ligne et à la disposition de tous librement:
https://vocaltractlab.de/index.php?page=vocaltractlab-download
VocalTractLab est un logiciel de synthèse articulatoire développé principalement par Peter Birkholz à la chaire de technologies de la parole et systèmes cognitifs de l’université de Dresde.
Au cours de mon postdoc j’ai travaillé à développer une version spéciale, VocalTractLab3D, qui inclut des simulations acoustiques 3Ds efficaces pilotées par une interface graphique. Contrairement aux simulations acoustiques couramment utilisées dans l’étude de la parole, qui reposent sur une approche 1D basée sur la function d’aire, les simulations 3Ds décrivent le champ acoustique dans toutes les dimensions de l’espace et prennent en compte la forme 3D précise du conduit vocal. Elles sont de fait plus précises, en particulier en haute fréquence (à partir d’environ 2-3 kHz). Leur limitation est cependant le temps de calcul. Dans notre projet nous avons travaillé à repousser cette limite et notre logiciel permet de réaliser ce type de simulation dans un temps raisonnable (environ 1 heure pour une géométrie statique avec une solution précise).
Une autre limitation courante des simulations 3Ds est la nécessité de maitriser des methods de simulations assez techniques tells que les éléments finis, différences finies ou autres. Cela passe souvent par l’utilisation d’un language de programmation. Nous avons également travaillé à repousser cette limite pour rendre accessible ce type de simulation au plus grand nombre: dans VocalTractLab3D ces simulations sont pilotées par une interface graphique et il n’est pas nécessaire de comprendre exactement comment fonctionne la méthode pour pouvoir calculer des fonctions de transfert ou des champs acoustiques.
Si suffisamment de personnes sont intéressées, je peux faire une présentation en ligne du logiciel, pour expliquer plus en detail en quoi il consiste, à quoi il peut servir et comment l’utiliser. Ecrivez-moi si cela vous intéresse.
N’hésitez pas également à me contacter si vous avez des questions par rapport à ce logiciel.
Bien à vous,
Rémi Blandin
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