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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 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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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 Description - This book presents the methods, tools and techniques that are currently being used to recognise (automatically) the affect, emotion, personality and everything else beyond linguistics (‘paralinguistics’) expressed by or embedded in human speech and language. - It is the first book to provide such a systematic survey of paralinguistics in speech and language processing. The technology described has evolved mainly from automatic speech and speaker recognition and processing, but also takes into account recent developments within speech signal processing, machine intelligence and data mining. - Moreover, the book offers a hands-on approach by integrating actual data sets, software, and open-source utilities which will make the book invaluable as a teaching tool and similarly useful for those professionals already in the field. Key features: - Provides an integrated presentation of basic research (in phonetics/linguistics and humanities) with state-of-the-art engineering approaches for speech signal processing and machine intelligence. - Explains the history and state of the art of all of the sub-fields which contribute to the topic of computational paralinguistics. - Covers the signal processing and machine learning aspects of the actual computational modelling of emotion and personality and explains the detection process from corpus collection to feature extraction and from model testing to system integration. - Details aspects of real-world system integration including distribution, weakly supervised learning and confidence measures. - Outlines machine learning approaches including static, dynamic and context-sensitive algorithms for classification and regression. - Includes a tutorial on freely available toolkits, such as the open-source ‘openEAR’ toolkit for emotion and affect recognition co-developed by one of the authors, and a listing of standard databases and feature sets used in the field to allow for immediate experimentation enabling the reader to build an emotion detection model on an existing corpus. Links: - The book: http://eu.wiley.com/WileyCDA/WileyTitle/productCd-1119971365.html - Table of Contents (pdf): http://media.wiley.com/product_data/excerpt/65/11199713/1119971365-16.pdf - Chapter01 (pdf): http://media.wiley.com/product_data/excerpt/65/11199713/1119971365-14.pdf 

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Foundations and Trends in Signal Processing (www.nowpublishers.com/sig) has published the following issue:   

Volume 7, Issue 3-4                                                                                                                                                                   
Deep Learning: Methods and Applications                                                               
By Li Deng and Dong Yu (Microsoft Research, USA)       
http://dx.doi.org/10.1561/2000000039                                       

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Tackling the Complexity in Speech

The present volume is meant to give the reader an impression of the range of questions and topics that are currently subject of international research in the discovery of complexity, the organization of complexity, and the modelling of complexity. These are the main sections of our volume. Each section includes four carefully selected chapters. They deal with facets of speech production, speech acoustics, and/or speech perception or recognition, place them in an integrated phonetic-phonological perspective, and relate them in more or less explicit ways to aspects of speech technology. Therefore, we hope that this volume can help speech scientists with traditional training in phonetics and phonology to keep up with the latest developments in speech technology. In the opposite direction, speech researchers starting from a technological perspective will hopefully get inspired by reading about the questions, phenomena, and communicative functions that are currently addressed in phonetics and phonology. Either way, the future of speech research lies in international, interdisciplinary collaborations, and our volume is meant to reflect and facilitate such collaborations.

https://e-shop.ff.cuni.cz/books/monographs_eng/opera_facultatis_philosophicae_eng/tackling_the_complexity_in_spee_-1153

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 'Robust Automatic Speech Recognition'

• The  first book that provides a comprehensive review on noise and reverberation robust speech recognition methods in the era of deep neural networks
• Connects robust speech recognition techniques to machine learning paradigms with rigorous mathematical treatment
• Provides elegant and structural ways to categorize and analyze noise-robust speech recognition techniques
• Written by leading researchers who have been actively working on the subject matter in both industrial and academic organizations for many years

https://na01.safelinks.protection.outlook.com/?url=http%3a%2f%2fstore.elsevier.com%2fRobust-Automatic-Speech-Recognition%2fJinyu-Li%2fisbn-9780128023983%2f.&data=01%7c01%7cygong%40exchange.microsoft.com%7c3bd27ec380c8427e97e208d2975aca2a%7c72f988bf86f141af91ab2d7cd011db47%7c1&sdata=PRRo3i4DYNV1rNmVlhPMaHa0pUN4oi%2b1khyjctDXxjU%3d

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Barbosa, P. A. and Madureira, S. Manual de Fonética Acústica Experimental. Aplicações a dados do português. 591 p. São Paulo: Cortez, 2015. [In Portuguese]     


http://www.cortezeditora.com.br/manual-de-fonetica-acustica-experimental-1599.aspx/p

This manual of Experimental Acoustic Phonetics is conceived for Undergraduate and Graduate classes on areas such as Acoustic Phonetics, Phonology, Communications Engineering, Music, Acoustic Physics, Speech Theraphy, among others.  Starting with a theoretical and methodological presentation of Acoustic Phonetics Theory and Techniques in five chapters,  including a chapter on experimental methods, the book follows with detailed acoustic analysis of all classes of sounds using audio files from both European and Brazilian Portuguese as data.
All analyses are explained step by step using Praat. The audiofiles are available on the book web site and can be downloaded.  All techniques can be applied to any language, of course. Proposed exercices at the end of each chapter allow the teacher o evaluate the student progress.

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Les entités nommées pour le traitement automatique des langues

Damien Nouvel, Inalco, Maud Ehrmann, EPFL
Sophie Rosset, CNRS  

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