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ISCApad #189 |
Saturday, March 15, 2014 by Chris Wellekens |
5-1-1 | Video archive of Odyssey Speaker and Language Recognition Workshop, Singapore 2012Odyssey Speaker and Language Recognition Workshop 2012, the workshop of ISCA SIG Speaker and Language Characterization, was held in Singapore on 25-28 June 2012. Odyssey 2012 is glad to announce that its video recordings have been included in the ISCA Video Archive. http://www.isca-speech.org/iscaweb/index.php/archive/video-archive
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5-1-2 | Tuomas Virtanen, Rita Singh, Bhiksha Raj (editors),Techniques for Noise Robustness in Automatic Speech Recognition,Wiley Techniques for Noise Robustness in Automatic Speech Recognition
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5-1-3 | Niebuhr, Olivier, Understanding Prosody:The Role of Context, Function and Communication Understanding Prosody: The Role of Context, Function and Communication Ed. by Niebuhr, Oliver Series:Language, Context and Cognition 13, De Gruyter http://www.degruyter.com/view/product/186201?format=G or http://linguistlist.org/pubs/books/get-book.cfm?BookID=63238
The volume represents a state-of-the-art snapshot of the research on prosody for phoneticians, linguists and speech technologists. It covers well-known models and languages. How are prosodies linked to speech sounds? What are the relations between prosody and grammar? What does speech perception tell us about prosody, particularly about the constituting elements of intonation and rhythm? The papers of the volume address questions like these with a special focus on how the notion of context-based coding, the knowledge of prosodic functions and the communicative embedding of prosodic elements can advance our understanding of prosody.
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5-1-4 | Albert Di Cristo: « La Prosodie de la Parole : Une Introduction », Editions de Boeck-Solal (296 p) Albert Di Cristo: « La Prosodie de la Parole : Une Introduction », Editions de Boeck-Solal (296 p).
Sommaire :
Avant –propos, Introduction, ;
Ch.1 : Eléments de définition ;
Ch 2. Situation de la prosodie dans le champ des sciences du langage et dans l’étude de la communication ;
Ch 3. La prosodie sur les deux versants de la communication orale interindividuelle (production et compréhension) ;
Ch 4. La prosodie et le cerveau ;
Ch 5. La matérialité de la prosodie ;
Ch 6. Les niveau d’analyse et de représentation de la prosodie ;
Ch 7. Les théories, les modèles de la prosodie et leurs appareils formels ;
Ch 8 La fonctionnalité plurielle de la prosodie ;
Ch 9. Les relations de la prosodie avec les sens ;
Epilogue.
Suggestions de lecture ;
Index des termes ;
Index des noms propres.
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5-1-5 | Pierre-Yves Oudeyer, 'Aux sources de la parole: auto-organisation et évolution', Odile Jacob Pierre-Yves Oudeyer, dir. rech. Inria, vient de publier 'Aux sources de la parole: auto-organisation et évolution', chez Odile Jacob (Sept. 2013).
Il discute de la question de l'évolution et de l'acquisition de la parole, chez l'enfant et chez les robots.
En faisant dialoguer biologie, linguistique, neurosciences et expériences robotiques,
ce livre étudie en particulier les phénomènes d'auto-organisation, permettant la formation spontanée de langues nouvelles dans une population d'individus.
Il présente en particulier des expériences dans lesquelles une population de robots numériques invente, forme, et négotie son propre système de parole
et explique comment de telles expériences robotiques peuvent nous aider à mieux comprendre l'homme.
Il présente aussi des expérimentations robotiques récentes, et à partir de perspectives nouvelles en intelligence artificielle, dans lesquelles des mécanismes de curiosité permettent à un robot de découvrir par lui-même son corps, les objets qui l'entourent, et finalement les interactions vocales avec ses pairs. C'est ainsi que s'auto-organise son propre développement cognitif, et qu'apparaissent des hypothèses nouvelles pour comprendre le développement chez l'enfant.
Site web du livre: http://goo.gl/A6EwTJ
Pierre-Yves Oudeyer,
Directeur de recherche, Inria
Responsable de l'équipe Flowers
Inria Bordeaux Sud-Ouest et Ensta-ParisTech, France
Twitter: https://twitter.com/pyoudeyer
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5-1-6 | Björn Schuller, Anton Batliner , Computational Paralinguistics: Emotion, Affect and Personality in Speech and Language Processing, Wiley, ISBN: 978-1-119-97136-8, 344 pages, November 2013
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5-2-1 | ELRA - Language Resources Catalogue - Update (2013-12) ***************************************************************** We are happy to announce that 1 new Speech Language Resource and 1 new Written Corpus are now available in our catalogue.
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5-2-2 | ELRA releases free Language Resources ELRA releases free Language Resources
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5-2-3 | LDC Newsletter (February 2014)
In this newsletter: Spring 2014 LDC Data Scholarship recipients! Membership fee savings and publications pipeline New LDC website enhancements coming soon New publications: GALE Arabic-English Parallel Aligned Treebank -- Broadcast News Part 2 King Saud University Arabic Speech Database NIST 2012 Open Machine Translation (OpenMT) Progress Test Five Language Source Spring 2014 LDC Data Scholarship recipients! LDC is pleased to announce the student recipients of the Spring 2014 LDC Data Scholarship program! This program provides university students with access to LDC data at no-cost. Students were asked to complete an application which consisted of a proposal describing their intended use of the data, as well as a letter of support from their thesis adviser. We received many solid applications and have chosen two proposals to support. The following students will receive no-cost copies of LDC data:
Membership fee savings and publications pipeline Members can still save on 2014 membership fees, but time is running out. Any organization which joins or renews membership for 2014 through Monday, March 3, 2014, is entitled to a 5% discount. Organizations which held membership for MY2013 can receive a 10% discount on fees provided they renew prior to March 3, 2014. Planned publications for this year include:
New LDC website enhancements coming soon
New publications (1) GALE Arabic-English Parallel Aligned Treebank -- Broadcast News Part 2 was developed by LDC and contains 141,058 tokens of word aligned Arabic and English parallel text with treebank annotations. This material was used as training data in the DARPA GALE (Global Autonomous Language Exploitation) program. Parallel aligned treebanks are treebanks annotated with morphological and syntactic structures aligned at the sentence level and the sub-sentence level. Such data sets are useful for natural language processing and related fields, including automatic word alignment system training and evaluation, transfer-rule extraction, word sense disambiguation, translation lexicon extraction and cultural heritage and cross-linguistic studies. With respect to machine translation system development, parallel aligned treebanks may improve system performance with enhanced syntactic parsers, better rules and knowledge about language pairs and reduced word error rate. In this release, the source Arabic data was translated into English. Arabic and English treebank annotations were performed independently. The parallel texts were then word aligned. The material in this corpus corresponds to a portion of the Arabic treebanked data in Arabic Treebank - Broadcast News v1.0 (LDC2012T07). The source data consists of Arabic broadcast news programming collected by LDC in 2007 and 2008. All data is encoded as UTF-8. A count of files, words, tokens and segments is below.
The purpose of the GALE word alignment task was to find correspondences between words, phrases or groups of words in a set of parallel texts. Arabic-English word alignment annotation consisted of the following tasks:
GALE Arabic-English Parallel Aligned Treebank -- Broadcast News Part 2 is distributed via web download. 2014 Subscription Members will automatically receive two copies of this data on disc. 2014 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for US$1750.
The corpus was designed principally for speaker recognition research. The speech sources are sentences, word lists, prose and question and answer sessions. Read speech text includes the following:
Spontaneous speech was captured through question and answer sessions between participants and project team members. Speakers responded to questions on general topics such as the weather and food. Each speaker was recorded in three different environments: a sound proof room, an office, and a cafeteria. The recordings were collected via microphone and mobile phone and averaged between 16-19 minutes. The data was verified for missing recordings, problems with the recording system or errors in the recording process. King Saud University Arabic Speech Database is distributed on one hard disk. 2014 Subscription Members will receive a copy of this data provided that they have completed the User License Agreement. 2014 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for US$2000.
(3) NIST 2012 Open Machine Translation (OpenMT) Progress Test Five Language Source was developed by NIST Multimodal Information Group. This release contains the evaluation sets (source data and human reference translations), DTD, scoring software, and evaluation plan for the OpenMT 2012 test for Arabic, Chinese, Dari, Farsi, and Korean to English on a parallel data set. The set is based on a subset of the Arabic-to-English and Chinese-to-English progress tests from the OpenMT 2008, 2009 and 2012 evaluations with new source data created by humans based on the English reference translation. The package was compiled, and scoring software was developed, at NIST, making use of newswire and web data and reference translations developed by the Linguistic Data Consortium and the Defense Language Institute Foreign Language Center. The objective of the OpenMT evaluation series is to support research in, and help advance the state of the art of, machine translation (MT) technologies -- technologies that translate text between human languages. Input may include all forms of text. The goal is for the output to be an adequate and fluent translation of the original. The 2012 task included the evaluation of five language pairs: Arabic-to-English, Chinese-to-English, Dari-to-English, Farsi-to-English and Korean-to-English in two source data styles. For general information about the NIST OpenMT evaluations, refer to the NIST OpenMT website. This evaluation kit includes a single Perl script (mteval-v13a.pl) that may be used to produce a translation quality score for one (or more) MT systems. The script works by comparing the system output translation with a set of (expert) reference translations of the same source text. Comparison is based on finding sequences of words in the reference translations that match word sequences in the system output translation. This release consists of 20 files, four for each of the five languages, presented in XML with an included DTD. The four files are source and reference data in the following two styles:
NIST 2012 Open Machine Translation (OpenMT) Progress Test Five Language Source is distributed via web download. 2014 Subscription Members will automatically receive two copies of this data on disc. 2014 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for US$150.
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5-2-4 | Appen ButlerHill
Appen ButlerHill A global leader in linguistic technology solutions RECENT CATALOG ADDITIONS—MARCH 2012 1. Speech Databases 1.1 Telephony
2. Pronunciation Lexica Appen Butler Hill has considerable experience in providing a variety of lexicon types. These include: Pronunciation Lexica providing phonemic representation, syllabification, and stress (primary and secondary as appropriate) Part-of-speech tagged Lexica providing grammatical and semantic labels Other reference text based materials including spelling/mis-spelling lists, spell-check dictionar-ies, mappings of colloquial language to standard forms, orthographic normalization lists. Over a period of 15 years, Appen Butler Hill has generated a significant volume of licensable material for a wide range of languages. For holdings information in a given language or to discuss any customized development efforts, please contact: sales@appenbutlerhill.com
4. Other Language Resources Morphological Analyzers – Farsi/Persian & Urdu Arabic Thesaurus Language Analysis Documentation – multiple languages
For additional information on these resources, please contact: sales@appenbutlerhill.com 5. Customized Requests and Package Configurations Appen Butler Hill is committed to providing a low risk, high quality, reliable solution and has worked in 130+ languages to-date supporting both large global corporations and Government organizations. We would be glad to discuss to any customized requests or package configurations and prepare a cus-tomized proposal to meet your needs.
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5-2-5 | OFROM 1er corpus de français de Suisse romande Nous souhaiterions vous signaler la mise en ligne d'OFROM, premier corpus de français parlé en Suisse romande. L'archive est, dans version actuelle, d'une durée d'environ 15 heures. Elle est transcrite en orthographe standard dans le logiciel Praat. Un concordancier permet d'y effectuer des recherches, et de télécharger les extraits sonores associés aux transcriptions.
Pour accéder aux données et consulter une description plus complète du corpus, nous vous invitons à vous rendre à l'adresse suivante : http://www.unine.ch/ofrom.
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5-2-6 | Real-world 16-channel noise recordings We are happy to announce the release of DEMAND, a set of real-world
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5-2-7 | Aide à la finalisation de corpus oraux ou multimodaux pour diffusion, valorisation et dépôt pérenne Aide à la finalisation de corpus oraux ou multimodaux pour diffusion, valorisation et dépôt pérenne
Le consortium IRCOM de la TGIR Corpus et l’EquipEx ORTOLANG s’associent pour proposer une aide technique et financière à la finalisation de corpus de données orales ou multimodales à des fins de diffusion et pérennisation par l’intermédiaire de l’EquipEx ORTOLANG. Cet appel ne concerne pas la création de nouveaux corpus mais la finalisation de corpus existants et non-disponibles de manière électronique. Par finalisation, nous entendons le dépôt auprès d’un entrepôt numérique public, et l’entrée dans un circuit d’archivage pérenne. De cette façon, les données de parole qui ont été enrichies par vos recherches vont pouvoir être réutilisées, citées et enrichies à leur tour de manière cumulative pour permettre le développement de nouvelles connaissances, selon les conditions d’utilisation que vous choisirez (sélection de licences d’utilisation correspondant à chacun des corpus déposés).
Cet appel d’offre est soumis à plusieurs conditions (voir ci-dessous) et l’aide financière par projet est limitée à 3000 euros. Les demandes seront traitées dans l’ordre où elles seront reçues par l’ IRCOM. Les demandes émanant d’EA ou de petites équipes ne disposant pas de support technique « corpus » seront traitées prioritairement. Les demandes sont à déposer du 1er septembre 2013 au 31 octobre 2013. La décision de financement relèvera du comité de pilotage d’IRCOM. Les demandes non traitées en 2013 sont susceptibles de l’être en 2014. Si vous avez des doutes quant à l’éligibilité de votre projet, n’hésitez pas à nous contacter pour que nous puissions étudier votre demande et adapter nos offres futures.
Pour palier la grande disparité dans les niveaux de compétences informatiques des personnes et groupes de travail produisant des corpus, L’ IRCOM propose une aide personnalisée à la finalisation de corpus. Celle-ci sera réalisée par un ingénieur IRCOM en fonction des demandes formulées et adaptées aux types de besoin, qu’ils soient techniques ou financiers.
Les conditions nécessaires pour proposer un corpus à finaliser et obtenir une aide d’IRCOM sont :
Les demandes peuvent concerner tout type de traitement : traitements de corpus quasi-finalisés (conversion, anonymisation), alignement de corpus déjà transcrits, conversion depuis des formats « traitement de textes », digitalisation de support ancien. Pour toute demande exigeant une intervention manuelle importante, les demandeurs devront s’investir en moyens humains ou financiers à la hauteur des moyens fournis par IRCOM et ORTOLANG.
IRCOM est conscient du caractère exceptionnel et exploratoire de cette démarche. Il convient également de rappeler que ce financement est réservé aux corpus déjà largement constitués et ne peuvent intervenir sur des créations ex-nihilo. Pour ces raisons de limitation de moyens, les propositions de corpus les plus avancés dans leur réalisation pourront être traitées en priorité, en accord avec le CP d’IRCOM. Il n’y a toutefois pas de limite « théorique » aux demandes pouvant être faites, IRCOM ayant la possibilité de rediriger les demandes qui ne relèvent pas de ses compétences vers d’autres interlocuteurs.
Les propositions de réponse à cet appel d’offre sont à envoyer à ircom.appel.corpus@gmail.com. Les propositions doivent utiliser le formulaire de deux pages figurant ci-dessous. Dans tous les cas, une réponse personnalisée sera renvoyée par IRCOM.
Ces propositions doivent présenter les corpus proposés, les données sur les droits d’utilisation et de propriétés et sur la nature des formats ou support utilisés.
Cet appel est organisé sous la responsabilité d’IRCOM avec la participation financière conjointe de IRCOM et l’EquipEx ORTOLANG.
Pour toute information complémentaire, nous rappelons que le site web de l'Ircom (http://ircom.corpus-ir.fr) est ouvert et propose des ressources à la communauté : glossaire, inventaire des unités et des corpus, ressources logicielles (tutoriaux, comparatifs, outils de conversion), activités des groupes de travail, actualités des formations, ... L'IRCOM invite les unités à inventorier leur corpus oraux et multimodaux - 70 projets déjà recensés - pour avoir une meilleure visibilité des ressources déjà disponibles même si elles ne sont pas toutes finalisées.
Le comité de pilotage IRCOM
Utiliser ce formulaire pour répondre à l’appel : Merci.
Réponse à l’appel à la finalisation de corpus oral ou multimodal
Nom du corpus :
Nom de la personne à contacter : Adresse email : Numéro de téléphone :
Nature des données de corpus :
Existe-t’il des enregistrements : Quel média ? Audio, vidéo, autre… Quelle est la longueur totale des enregistrements ? Nombre de cassettes, nombre d’heures, etc. Quel type de support ? Quel format (si connu) ?
Existe-t’il des transcriptions : Quel format ? (papier, traitement de texte, logiciel de transcription) Quelle quantité (en heures, nombre de mots, ou nombre de transcriptions) ?
Disposez vous de métadonnées (présentation des droits d’auteurs et d’usage) ?
Disposez-vous d’une description précise des personnes enregistrées ?
Disposez-vous d’une attestation de consentement éclairé pour les personnes ayant été enregistrées ? En quelle année (environ) les enregistrements ont eu lieu ?
Quelle est la langue des enregistrements ?
Le corpus comprend-il des enregistrements d’enfants ou de personnes ayant un trouble du langage ou une pathologie ? Si oui, de quelle population s’agit-il ?
Dans un souci d’efficacité et pour vous conseiller dans les meilleurs délais, il nous faut disposer d’exemples des transcriptions ou des enregistrements en votre possession. Nous vous contacterons à ce sujet, mais vous pouvez d’ores et déjà nous adresser par courrier électronique un exemple des données dont vous disposez (transcriptions, métadonnées, adresse de page web contenant les enregistrements).
Nous vous remercions par avance de l’intérêt que vous porterez à notre proposition. Pour toutes informations complémentaires veuillez contacter Martine Toda martine.toda@ling.cnrs.fr ou à ircom.appel.corpus@gmail.com.
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5-2-8 | Rhapsodie: un Treebank prosodique et syntaxique de français parlé Rhapsodie: un Treebank prosodique et syntaxique de français parlé
Nous avons le plaisir d'annoncer que la ressource Rhapsodie, Corpus de français parlé annoté pour la prosodie et la syntaxe, est désormais disponible sur http://www.projet-rhapsodie.fr/
Le treebank Rhapsodie est composé de 57 échantillons sonores (5 minutes en moyenne, au total 3h de parole, 33000 mots) dotés d’une transcription orthographique et phonétique alignées au son.
Il s'agit d’une ressource de français parlé multi genres (parole privée et publique ; monologues et dialogues ; entretiens en face à face vs radiodiffusion, parole plus ou moins interactive et plus ou moins planifiée, séquences descriptives, argumentatives, oratoires et procédurales) articulée autour de sources externes (enregistrements extraits de projets antérieurs, en accord avec les concepteurs initiaux) et internes. Nous tenons en particulier à remercier les responsables des projets CFPP2000, PFC, ESLO, C-Prom ainsi que Mathieu Avanzi, Anne Lacheret, Piet Mertens et Nicolas Obin.
Les échantillons sonores (wave & MP3, pitch nettoyé et lissé), les transcriptions orthographiques (txt), les annotations macrosyntaxiques (txt), les annotations prosodiques (xml, textgrid) ainsi que les metadonnées (xml & html) sont téléchargeables librement selon les termes de la licence Creative Commons Attribution - Pas d’utilisation commerciale - Partage dans les mêmes conditions 3.0 France. Les annotations microsyntaxiques seront disponibles prochainement Les métadonnées sont également explorables en ligne grâce à un browser. Les tutoriels pour la transcription, les annotations et les requêtes sont disponibles sur le site Rhapsodie. Enfin, L’annotation prosodique est interrogeable en ligne grâce au langage de requêtes Rhapsodie QL. L'équipe Ressource Rhapsodie (Modyco, Université Paris Ouest Nanterre) Sylvain Kahane, Anne Lacheret, Paola Pietrandrea, Atanas Tchobanov, Arthur Truong. Partenaires : IRCAM (Paris), LATTICE (Paris), LPL (Aix-en-Provence), CLLE-ERSS (Toulouse).
******************************************************** Rhapsodie: a Prosodic and Syntactic Treebank for Spoken French We are pleased to announce that Rhapsodie, a syntactic and prosodic treebank of spoken French created with the aim of modeling the interface between prosody, syntax and discourse in spoken French is now available at http://www.projet-rhapsodie.fr/ The Rhapsodie treebank is made up of 57 short samples of spoken French (5 minutes long on average, amounting to 3 hours of speech and a 33 000 word corpus) endowed with an orthographical phoneme-aligned transcription . The corpus is representative of different genres (private and public speech; monologues and dialogues; face-to-face interviews and broadcasts; more or less interactive discourse; descriptive, argumentative and procedural samples, variations in planning type). The corpus samples have been mainly drawn from existing corpora of spoken French and partially created within the frame of theRhapsodie project. We would especially like to thank the coordinators of the CFPP2000, PFC, ESLO, C-Prom projects as well as Piet Mertens, Mathieu Avanzi, Anne Lacheret and Nicolas Obin. The sound samples (waves, MP3, cleaned and stylized pitch), the orthographic transcriptions (txt), the macrosyntactic annotations (txt), the prosodic annotations (xml, textgrid) as well as the metadata (xml and html) can be freely downloaded under the terms of the Creative Commons licence Attribution - Noncommercial - Share Alike 3.0 France. Microsyntactic annotation will be available soon. The metadata are searchable on line through a browser. The prosodic annotation can be explored on line through the Rhapsodie Query Language. The tutorials of transcription, annotations and Rhapsodie Query Language are available on the site.
The Rhapsodie team (Modyco, Université Paris Ouest Nanterre : Sylvain Kahane, Anne Lacheret, Paola Pietrandrea, Atanas Tchobanov, Arthur Truong. Partners: IRCAM (Paris), LATTICE (Paris), LPL (Aix-en-Provence),CLLE-ERSS (Toulouse).
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5-2-9 | COVAREP: A Cooperative Voice Analysis Repository for Speech Technologies ======================
CALL for contributions
======================
We are pleased to announce the creation of an open-source repository of advanced speech processing algorithms called COVAREP (A Cooperative Voice Analysis Repository for Speech Technologies). COVAREP has been created as a GitHub project (https://github.com/covarep/covarep) where researchers in speech processing can store original implementations of published algorithms.
Over the past few decades a vast array of advanced speech processing algorithms have been developed, often offering significant improvements over the existing state-of-the-art. Such algorithms can have a reasonably high degree of complexity and, hence, can be difficult to accurately re-implement based on article descriptions. Another issue is the so-called 'bug magnet effect' with re-implementations frequently having significant differences from the original. The consequence of all this has been that many promising developments have been under-exploited or discarded, with researchers tending to stick to conventional analysis methods.
By developing the COVAREP repository we are hoping to address this by encouraging authors to include original implementations of their algorithms, thus resulting in a single de facto version for the speech community to refer to.
We envisage a range of benefits to the repository:
1) Reproducible research: COVAREP will allow fairer comparison of algorithms in published articles.
2) Encouraged usage: the free availability of these algorithms will encourage researchers from a wide range of speech-related disciplines (both in academia and industry) to exploit them for their own applications.
3) Feedback: as a GitHub project users will be able to offer comments on algorithms, report bugs, suggest improvements etc.
SCOPE
We welcome contributions from a wide range of speech processing areas, including (but not limited to): Speech analysis, synthesis, conversion, transformation, enhancement, speech quality, glottal source/voice quality analysis, etc.
REQUIREMENTS
In order to achieve a reasonable standard of consistency and homogeneity across algorithms we have compiled a list of requirements for prospective contributors to the repository. However, we intend the list of the requirements not to be so strict as to discourage contributions.
LICENCE
Getting contributing institutions to agree to a homogenous IP policy would be close to impossible. As a result COVAREP is a repository and not a toolbox, and each algorithm will have its own licence associated with it. Though flexible to different licence types, contributions will need to have a licence which is compatible with the repository, i.e. {GPL, LGPL, X11, Apache, MIT} or similar. We would encourage contributors to try to obtain LGPL licences from their institutions in order to be more industry friendly.
CONTRIBUTE!
We believe that the COVAREP repository has a great potential benefit to the speech research community and we hope that you will consider contributing your published algorithms to it. If you have any questions, comments issues etc regarding COVAREP please contact us on one of the email addresses below. Please forward this email to others who may be interested.
Existing contributions include: algorithms for spectral envelope modelling, adaptive sinusoidal modelling, fundamental frequncy/voicing decision/glottal closure instant detection algorithms, methods for detecting non-modal phonation types etc.
Gilles Degottex <degottex@csd.uoc.gr>, John Kane <kanejo@tcd.ie>, Thomas Drugman <thomas.drugman@umons.ac.be>, Tuomo Raitio <tuomo.raitio@aalto.fi>, Stefan Scherer <scherer@ict.usc.edu>
Website - http://covarep.github.io/covarep
GitHub - https://github.com/covarep/covarep
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5-2-10 | Annotation of “Hannah and her sisters” by Woody Allen. We have created and made publicly available a dense audio-visual person-oriented ground-truth annotation of a feature movie (100 minutes long): “Hannah and her sisters” by Woody Allen. Jean-Ronan Vigouroux, Louis Chevallier Patrick Pérez Technicolor Research & Innovation
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5-2-11 | French TTS Text to Speech Synthesis:
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5-2-12 | Google 's Language Model benchmark A LM benchmark is available at: https://code.google.com/p/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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5-2-13 | International Standard Language Resource Number (ISLRN) (ELRA Press release) Press Release - Immediate - Paris, France, December 13, 2013 Establishing the International Standard Language Resource Number (ISLRN) 12 major NLP organisations announce the establishment of the ISLRN, a Persistent Unique Identifier, to be assigned to each Language Resource. On November 18, 2013, 12 NLP organisations have agreed to announce the establishment of the International Standard Language Resource Number (ISLRN), a Persistent Unique Identifier, to be assigned to each Language Resource. Experiment replicability, an essential feature of scientific work, would be enhanced by such unique identifier. Set up by ELRA, LDC and AFNLP/Oriental-COCOSDA, the ISLRN Portal will provide unique identifiers using a standardised nomenclature, as a service free of charge for all Language Resource providers. It will be supervised by a steering committee composed of representatives of participating organisations and enlarged whenever necessary. More information on ELRA and the ISLRN, please contact: Khalid Choukri choukri@elda.org More information on ELDA, please contact: Hélène Mazo mazo@elda.org ELRA 55-57, rue Brillat Savarin 75013 Paris (France) Tel.: +33 1 43 13 33 33 Fax: +33 1 43 13 33 30
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5-2-14 | Speechocean March 2014 update Speechocean March 2014 update:
Speechocean: A global language resources and data services supplier
has over 500 large-scale databases available in 110+ languages and accents with the platform of desktop, in-car, telephony and tablet PC. Our data repository is enormous and diversified, which includes ASR Databases, TTS Databases, Lexica, Text Corpora, etc.
Speechocean is glad to announce that more resources have been released: ASR DatabasesSpeechocean provides 110+ regional languages corpora, available in a variety of formats, situational styles, scene environments and platform systems, covering In-car speech recognition corpora, mobile phone speech recognition corpora, fixed-line speech recognition corpora, desktop speech recognition corpora, etc. This month we released more Asian languages databases which were made for the tuning and testing purpose of speech recognition systems for speech ASR applications.
Chinese Mandarin Speech Recognition Database ---- (In-Car)-100 Speakers ID: King-ASR-122 This database was collected in China Mainland. It contains the voices of 100 different native speakers (50 males, 50 females) who were balanced according to age(mainly 18 – 30(62),31 – 45(28),46 – 60(10)), gender (Male 50%, Female 50%) and regional accents (Northern 60%, Wu 10%, Xiang 5%, Gan 5%, Kejia 5%, Min 5%, Cantonese 10%).
Each utterance is stored in a separate file and each signal file is accompanied by an ASCII SAM label file which contains the relevant descriptive information. A pronunciation lexicon with a phonemic transcription in SAMPA is also included. All the data was transcribed and labeled. Japanese Speech Recognition Database ---- (In-Car)-800 Speakers ID: King-ASR-125 This Japan In-car Speech database was collected in Japan and contains the voices of 800 different native speakers who were demographically balanced according to Age (16-30, 31-45, and 46-60), Gender (400±5% males, 400±5% females) and Dialectical Region. The script was specially designed to provide material for both training and testing of many classes of speech recognizers which contains 16 general categories and more than 50 specific sub-categories. Each speaker was recorded under three driving environments (parked, city driving and highway driving) with recording conditions such as fan on/off and window up/down. A total of 300 utterances were recorded for each speaker in two of three driving environments (150 utterances and 10 spontaneous utterances per environment).
Japanese Speech Recognition Database ---- Conversation (Telephony)-201 Speakers This Japanese Speech Recognition database was collected in Japan and contains the voices of 201 different native speakers who were demographic balanced according to age distribution (16-28,29-60), Gender, Dialectical Regions. The corpus contains 100 pairs of spontaneous dialog speech data which were from 201 speakers. Each pair of speech consists of 3 audio files: two of them from single speaker separately and the other is from the mixed channel. The three files were recorded simultaneously. The pure recording time of mixed channel is about 104.8 hours. 33 topics were contained in this database.
There are 7,009 audio files which were saved as uncompressed PCM files. All the speech data was transcribed and labeled. 1.3 MobileKorean Speech Recognition Database—(Mobile)--1023 Speakers ID: King-ASR-137 The Korean mobile speech Recognition database which was collected in Korea, contains the voices of 1023 different native speakers (510±5%males, 513±5% females) who were balanced according to age (mainly 16 – 30,31 – 45,46 – 60), Gender and regional accents (for the details, please see the technical document).
Chinese Mandarin Speech Recognition Database---Sentences (Mobile) - (5048 Speakers) ID: King-ASR-216 This database is a desktop speech database collected by Speechocean which is performed in a quiet environment in China. This database is one of our databases of Speech Data ----Mobile Project (SDM) which contains the database collections in 30 languages presently.
The script was specially designed to provide material for both training and testing of many classes of speech recognizers. The script of each speaker contains 300 sentences which were randomly selected from a pool of sentences specially designed. Each speaker will be recorded as naturally as possible in quiet environment through Popular Mobile Phones such as of iPhones, HTC Samsung, MOTO and etc. which cover the platforms of ios, android and window mobile. The speech data are stored as sequences of 16 kHz, 16 bit and uncompressed PCM format. All the speech was manually transcribed and labeled. A pronunciation lexicon with a phonemic transcription in Pinyin is also included.
Indonesian Speech Recognition Database ---- Sentences (Desktop)-200 Speakers ID: King-ASR-061 This Indonesian Speech Recognition database was collected in Indonesia and contains the voices of 200 different native speakers who were demographic balanced according to age distribution (16–30, 31–45, 46–60) and Gender. It contains 239267 audio files with about 460.94 hours of recording. Each speaker uttered 300 sentences in a quiet office room. The whole data has been proofread manually with precise data labeling. Urdu Speech Recognition Database ----Sentences (Desktop)-200 Speakers ID: King-ASR-063 This Urdu Speech Recognition database, which was collected in Pakistan, contains the voices of 200 native speakers who were demographic balanced according to age distribution (16–60), gender, dialectical Regions, there were 241,354 audio files which were saved as uncompressed PCM files. All the speech data was transcribed and labeled. Vietnamese Speech Recognition Database ----Sentences (Desktop)-200 Speakers ID: King-ASR-074 This Vietnamese Speech Recognition database, which was collected in Vietnam, contains the voices of 200 native speakers who were demographic balanced according to age distribution (16–60), Gender, Dialectical Regions, there were 263,204 audio files which were saved as uncompressed PCM files. All the speech data was transcribed and labeled.
Speechocean licenses a variety of databases in more than 40 languages for speech synthesis broadcasting speech, emotional speech, etc. which can be used in different algorithms.
European Portuguese Speech Corpus for TTS (Female) ID: King-TTS-017 The European Portuguese (pt-PT) Speech Corpus consists native Portuguese female professional broadcaster (Female, 32 years old) recorded in a studio with high SNR (>35dB) over two channels (Shure SM15 microphone and Electroglottography (EGG) sensor).
The Corpus includes the following sub-corpora:
All reading prompts are manually revised and prosody annotations were made according to real speech. All speech data are segmented and labeled on phone level. Pronunciation lexicon and pitch extract from EEG can also be provided based on demands
Speechocean licenses many kinds of text corpora in many languages which is superb for language model training.
Speechocean builds pronunciation lexica in many languages which can be licensed to customers.
Contact Information Xianfeng Cheng Business Manager of Commercial Department Tel: +86-10-62660928; +86-10-62660053 ext.8080 Cell phone: +86 13681432590 Skype: xianfeng.cheng1 Email: chengxianfeng@speechocean.com; cxfxy0cxfxy0@gmail.com Website: www.speechocean.com
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5-3-1 | ROCme!: a free tool for audio corpora recording and management ROCme!: nouveau logiciel gratuit pour l'enregistrement et la gestion de corpus audio.
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5-3-2 | VocalTractLab 2.0 : A tool for articulatory speech synthesis VocalTractLab 2.0 : A tool for articulatory speech synthesis
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5-3-3 | Voice analysis toolkit After just completing my PhD I have made the algorithms I have developed during it available online: https://github.com/covarep/covarep
The so-called Voice Analysis Toolkit contains algorithms for glottal source and voice quality analysis. In making the code available online I hope that people in the speech processing community can benefit from it. I would really appreciate if you could include a link to this in the software section of the next ISCApad (section 5-3).
thanks for this.
John Researcher
Centre for Language and Communication Studies,
School of Linguistics, Speech and Communication Sciences, Trinity College Dublin, College Green Dublin 2 Phone: (+353) 1 896 1348 Website: http://www.tcd.ie/slscs/postgraduate/phd-masters-research/student-pages/johnkane.php Check out our workshop!! http://muster.ucd.ie/workshops/iast/
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5-3-4 | Bob signal-processing and machine learning toolbox (v.1.2..0)
It is developed by the Biometrics
Group at Idiap in Switzerland. -- ------------------- Dr. Elie Khoury Post Doctorant Biometric Person Recognition Group IDIAP Research Institute (Switzerland) Tel : +41 27 721 77 23
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5-3-5 | 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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