Satoshi Nakamura – författare

Incorporating Knowledge Sources into Statistical Speech Recognition addresses the problem of developing efficient automatic speech recognition (ASR) systems, which maintain a balance between utilizing a wide knowledge of speech variability, while keeping the training / recognition effort feasible and improving speech recognition performance. The book provides an efficient general framework to incorporate additional knowledge sources into state-of-the-art statistical ASR systems. It can be applied to many existing ASR problems with their respective model-based likelihood functions in flexible ways.

Spoken Dialogue Systems Technology and Design covers key topics in the field of spoken language dialogue interaction from a variety of leading researchers. It brings together several perspectives in the areas of corpus annotation and analysis, dialogue system construction, as well as theoretical perspectives on communicative intention, context-based generation, and modelling of discourse structure. These topics are all part of the general research and development within the area of discourse and dialogue with an emphasis on dialogue systems; corpora and corpus tools and semantic and pragmatic modelling of discourse and dialogue.

Spoken Dialogue Systems Technology and Design covers key topics in the field of spoken language dialogue interaction from a variety of leading researchers. It brings together several perspectives in the areas of corpus annotation and analysis, dialogue system construction, as well as theoretical perspectives on communicative intention, context-based generation, and modelling of discourse structure. These topics are all part of the general research and development within the area of discourse and dialogue with an emphasis on dialogue systems; corpora and corpus tools and semantic and pragmatic modelling of discourse and dialogue.

It is our great pleasure to welcome you to the 2nd International Workshop on Spoken Dialogue Systems Technology (IWSDS), which was held, as a satellite event of INTERSPEECH 2010, at Gotemba Kogen Resort in the Fuji area, Japan, October 1-2, 2010. The annual workshop brings together researchers from all over the world working in the ?eld of spoken dialogue systems. It provides an international - rum for the presentation of research and applications and for lively discussions among researchers as well as industrialists. Building on the success of IWSDS 2009Irsee,Germany,thisyear'sworkshopdesignated"SpokenDialogueSystems for Ambient Environments" as a special theme of discussion. We also enco- aged discussions of common issues of spoken dialogue systems including but not limited to: - Speech recognition and semantic analysis - Dialogue management - Adaptive dialogue modelling - Recognition of emotions from speech, gestures, facial expressions and ph- iological data - User modelling - Planning and reasoning capabilities for coordinationand con?ict description - Con?ict resolution in complex multi-level decisions - Multi-modality such as graphics, gesture and speech for input and output - Fusion and information management - Learning and adaptability - Visual processing and recognition for advanced human-computer interaction - Databases and corpora - Evaluation strategies and paradigms - Prototypes and products The workshop program consisted of 22 regular papers and 2 invited keynote talks.This year, we were pleased to have two keynote speakers: Prof. Ram' on L' opez-C' ozar, Universidad de Granada, Spain and Prof. Tetsunori Kobayashi, Waseda University, Japan.

In this work, the authors present a fully statistical approach to model non--native speakers' pronunciation. Second-language speakers pronounce words in multiple different ways compared to the native speakers. Those deviations, may it be phoneme substitutions, deletions or insertions, can be modelled automatically with the new method presented here.The methods is based on a discrete hidden Markov model as a word pronunciation model, initialized on a standard pronunciation dictionary. The implementation and functionality of the methodology has been proven and verified with a test set of non-native English in the regarding accent.The book is written for researchers with a professional interest in phonetics and automatic speech and speaker recognition.

In this work, the authors present a fully statistical approach to model non--native speakers' pronunciation. Second-language speakers pronounce words in multiple different ways compared to the native speakers. Those deviations, may it be phoneme substitutions, deletions or insertions, can be modelled automatically with the new method presented here.The methods is based on a discrete hidden Markov model as a word pronunciation model, initialized on a standard pronunciation dictionary. The implementation and functionality of the methodology has been proven and verified with a test set of non-native English in the regarding accent.The book is written for researchers with a professional interest in phonetics and automatic speech and speaker recognition.

This book compiles and presents a synopsis on current global research efforts to push forward the state of the art in dialogue technologies, including advances to the classical problems of dialogue management, language generation, question answering, human–robot interaction, chatbots design and evaluation, as well as topics related to the human nature of the conversational phenomena such as humour, social context, specific applications for e-health, understanding, and awareness

This book compiles and presents a synopsis on current global research efforts to push forward the state of the art in dialogue technologies, including advances to the classical problems of dialogue management, language generation, question answering, human–robot interaction, chatbots design and evaluation, as well as topics related to the human nature of the conversational phenomena such as humour, social context, specific applications for e-health, understanding, and awareness