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ISCApad #247 |
| Friday, January 18, 2019 by Chris Wellekens |
5 Resources
| 5-1-1 | R.Fuchs, 'Speech Rhythm in Varieties of English' , Springer R.Fuchs, 'Speech Rhythm in Varieties of English' has appeared with Springer, in the 'Prosody, Phonology and Phonetics' series: https://www.springer.com/gp/book/9783662478172
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| 5-1-2 | Pejman Mowlaee et al., 'Phase-Aware Signal Processing in Speech Communication: Theory and Practice', Wiley 2016Phase-Aware Signal Processing in Speech Communication: Theory and Practice
http://eu.wiley.com/WileyCDA/WileyTitle/productCd-1119238811.html
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| 5-1-3 | Jean Caelen, Anne Xuereb, 'Dialogue : altérité, interaction, énaction'
Jean Caelen,Anne Xuereb Dialogue : altérité, interaction, énaction Editions universitaires européennes
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| 5-1-4 | Bäckström, Tom (with Guillaume Fuchs, Sascha Disch, Christian Uhle and Jeremie Lecomte), 'Speech Coding with Code-Excited Linear Prediction', Springer
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| 5-1-5 | Shinji Watanabe, Marc Delcroix, Florian Metze, John R. Hershey (Eds), 'New Era for Robust Seech Recognition', Springer. Shinji Watanabe, Marc Delcroix, Florian Metze, John R. Hershey (Eds), 'New Era for Robust Seech Recognition', Springer. https://link.springer.com/book/10.1007%2F978-3-319-64680-0
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| 5-1-6 | Fabrice Marsac, Rudolph Sock, CONSÉCUTIVITÉ ET SIMULTANÉITÉ en Linguistique, Langues et Parole, L'Harmattan,France Nous avons le plaisir de vous annoncer la parution du volume thématique « CONSÉCUTIVITÉ ET SIMULTANÉITÉ en Linguistique, Langues et Parole » dans la Collection Dixit Grammatica (L’Harmattan, France) :
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| 5-1-7 | Emmanuel Vincent (Editor), Tuomas Virtanen (Editor), Sharon Gannot (Editor), 'Audio Source Separation and Speech Enhancement', Wiley Emmanuel Vincent (Editor), Tuomas Virtanen (Editor), Sharon Gannot (Editor), Audio Source Separation and Speech Enhancement:
ISBN: 978-1-119-27989-1 October 2018 504 pages
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| 5-1-8 | Jen-Tzung Chien, 'Source Separation and Machine Learning', Academic Press Jen-Tzung Chien, 'Source Separation and Machine Learning', Academic Press
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| 5-1-9 | Ingo Feldhausen, « Methods in prosody: A Romance language perspective », Language Science Press (open access) Nous sommes heureux de vous annoncer la parution d'un recueil validé par un comité de lecture et consacré aux méthodes de recherche en prosodie. Cet ouvrage est intitulé « Methods in prosody: A Romance language perspective ». Il est publié par Language Science Press, une maison d’édition open access. Le livre peut-être téléchargé gratuitement en cliquant sur le lien suivant : http://langsci-press.org/catalog/book/183 La table des matières est la suivante : --------------------------------------------------------------------------------------------------------- Introduction Foreword I Large corpora and spontaneous speech 1) Using large corpora and computational tools to describe prosody: An 2) Intonation of pronominal subjects in Porteño Spanish: Analysis of II Approaches to prosodic analysis 3) Multimodal analyses of audio-visual information: Some methods and 4) The realizational coefficient: Devising a method for empirically 5) On the role of prosody in disambiguating wh-exclamatives and III Elicitation methods 6) The Discourse Completion Task in Romance prosody research: Status 7) Describing the intonation of speech acts in Brazilian Portuguese: Indexes 263 --------------------------------------------------------------------------------------------------------- N'hésitez pas à diffuser la parution de cet ouvrage auprès de vos collègues qui pourraient s'y intéresser. Bien cordialement, Ingo Feldhausen
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| 5-2-1 | Linguistic Data Consortium (LDC) update (December 2018) In this newsletter:
LDC Membership Discounts for MY2019 Still Available
Spring 2019 LDC Data Scholarship Program - deadline approaching
New publications:
LDC Membership Discounts for MY2019 Still Available
Join LDC while membership savings are still available. Now through March 1, 2019, renewing MY2018 members will receive a 10% discount off the membership fee. New or non-consecutive member organizations will receive a 5% discount. Membership remains the most economical way to access LDC releases. Visit Join LDC for details on membership options and benefits.
Spring 2019 LDC Data Scholarship Program - deadline approaching
Students can apply for the Spring 2019 Data Scholarship Program now through January 15, 2019. The LDC Data Scholarship program provides students with access to LDC data at no cost. For more information on application requirements and program rules, please visit LDC Data Scholarships.
New publications:
(1) HUB5 Mandarin Telephone Speech and Transcripts Second Edition was developed by LDC in support of US government projects for language recognition and Large Vocabulary Conversational Speech Recognition (LVCSR). The first edition was released by LDC in two data sets, HUB5 Mandarin Telephone Speech Corpus (LDC98S69) and HUB5 Mandarin Transcripts (LDC98T26). This second edition merges the speech and transcript releases, updates the audio format, and adds Pinyin transcripts, forced alignment, and updated documentation and metadata.
This corpus contains approximately 19 hours of Mandarin speech from 42 unscripted telephone conversations between native speakers of Mandarin from CALLFRIEND Mandarin Chinese-Mainland Dialect (LDC96S55), which has also been released in a second, updated edition (LDC2018S09) and (2) associated transcripts of contiguous 5-30 minute segments from those telephone conversations.
Participants could speak with a person of their choice on any topic; most called family members and friends. The recorded conversations lasted up to 30 minutes. Transcripts were created manually by native Mandarin speakers in the GB2312 encoding schema. This release includes Pinyin transcripts and the original transcripts, both in UTF-8 format.
HUB5 Mandarin Telephone Speech and Transcripts Second Edition is available via web download.
2018 Subscription Members will automatically receive copies of this corpus. 2018 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for $2500.
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(2) Nautilus Speaker Characterization was developed at the Technical University of Berlin and is comprised of approximately 155 hours of conversational speech from 300 German speakers aged 18 to 35 years (126 males and 174 females) with no marked dialect or accent, recorded in an acoustically-isolated room. The corpus was designed to support research on the detection of speaker social characteristics, such as personality, charisma, and voice attractiveness.
Four scripted and four semi-spontaneous dialogs simulating telephone call inquiries were elicited from the speakers. Additionally, spontaneous neutral and emotional speech utterances (predominantly excitement or frustration) and questions were produced.
Speech corresponding to one of the semi-spontaneous dialogs was evaluated with respect to 34 continuous numeric labels of perceived interpersonal speaker characteristics (such as likable, attractive, competent, childish). For a set of 20 selected 'extreme' speakers evaluated for their warmth-attractiveness, 34 naive voice descriptions (such as bright, creaky, articulate, melodious) were also evaluated. The corpus contains all labels, together with the speech recordings and the speakers' metadata (e.g., age, gender, place of birth, chronological places of residence and duration of stay, parents' place of birth, self-assessed personality).
Nautilus Speaker Characterization is available via web download.
2018 Subscription Members will receive copies of this corpus provided they have submitted a completed copy of the special license agreement. 2018 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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(3) TAC Relation Extraction Dataset (TACRED) was developed by The Stanford NLP Group and is a large-scale relation extraction dataset with 106,264 examples built over English newswire and web text used in the NIST TAC KBP English slot filling evaluations during the period 2009-2014. The annotations were derived from TAC KBP relation types (see the guidelines), from human annotations developed by LDC and from crowdsourcing using Mechanical Turk.
Source corpora used for this dataset were TAC KBP Comprehensive English Source Corpora 2009-2014 (LDC2018T03) and TAC KBP English Regular Slot Filling - Comprehensive Training and Evaluation Data 2009-2014 (LDC2018T22). For detailed information about the dataset and benchmark results, please refer to the TACRED paper.
TAC Relation Extraction Dataset is available via web download.
2018 Subscription Members will automatically receive copies of this corpus. 2018 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for $25.
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| 5-2-2 | ELRA - 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 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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| 5-2-3 | Speechocean – update (November 2018)
Spanish ASR & TTS Corpus --- Speechocean
Speechocean: The World’s Leading A.I. Data Resource & Service Supplier
At present, we can provide data services with 110+ languages and dialects across the world. For more detailed information, please visit our website: http://kingline.speechocean.com
Spanish ASR & TTS Corpus
More Information
About ASR Corpus…
About TTS Corpus…
Contact Information: Name: Xianfeng Cheng Position: Vice President Tel: +86-10-62660928; +86-10-62660053 ext.8080 Mobile: +86-13681432590 Skype: xianfeng.cheng1 Email: chengxianfeng@speechocean.com Website: www.speechocean.com http://kingline.speechocean.com
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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.
1, Speech data collection 2, Speech data synthesis 3, Speech data transcription I’ve attached our company introduction as reference, as well as available speech data lists as follows:
If you find any particular interested datasets, we could provide you samples with costs too.
Regards
Runze Zhao Oversea Sales Manager | Datatang Technology China M: +86 185 1698 2583 18 Zhongguancun St. Kemao Building Tower B 18F Beijing 100190
US M: +1 617 763 4722 640 W California Ave, Suite 210 Sunnyvale, CA 94086
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| 5-2-10 | Fearless 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.
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| 5-2-11 | 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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| 5-3-1 | Release of the version 2 of FASST (Flexible Audio Source Separation Toolbox).Release of the version 2 of FASST (Flexible Audio Source Separation Toolbox). http://bass-db.gforge.inria.fr/fasst/ This toolbox is intended to speed up the conception and to automate the implementation of new model-based audio source separation algorithms. It has the following additions compared to version 1: * Core in C++ * User scripts in MATLAB or python * Speedup * Multichannel audio input We provide 2 examples: 1. two-channel instantaneous NMF 2. real-world speech enhancement (2nd CHiME Challenge, Track 1)
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| 5-3-2 | 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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| 5-3-3 | 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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| 5-3-4 | 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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| 5-3-5 | 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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| 5-3-6 | Clickable map - Illustrations of the IPA Clickable map - Illustrations of the IPA
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| 5-3-7 | LIG-Aikuma running on mobile phones and tablets
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| 5-3-8 | 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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