Spoken Multimodal Human-Computer Dialogue in Mobile by Minker W. (Ed), Dybkjaer L. (Ed), Buhler D. (Ed)

By Minker W. (Ed), Dybkjaer L. (Ed), Buhler D. (Ed)

The continued migration of computing and data entry from desk bound environments to cellular computing units for eventual use in cellular environments, similar to own electronic Assistants (PDAs), capsule computers, subsequent iteration cell phones, and in-car driving force information platforms, poses severe demanding situations for traditional human-computer interplay. Spoken discussion is a key think about making sure ordinary and common interplay with such units that are intended not just for machine experts, but additionally for daily users.Speech helps hands-free and eyes-free operation, and turns into a key replacement interplay mode in cellular environments, e.g. in autos the place motive force distraction by means of operated by hand units could be a major challenge. nevertheless, using cellular units in public locations, might make the potential of utilizing substitute modalities almost certainly together with speech, reminiscent of pictures output and gesture enter, optimal as a result of e.g. privateness concerns. Researchers' curiosity is gradually turning to the mixing of speech with different modalities reminiscent of gesture enter and pics output, partially to house extra effective interplay and in part to deal with diverse person preferences.This book:-combines assessment chapters of key components in spoken multimodal discussion (systems and parts, architectures, and assessment) with chapters focussed on specific functions or difficulties within the field;-focuses at the impact of our surroundings while construction and comparing an program.

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Extra info for Spoken Multimodal Human-Computer Dialogue in Mobile Environments

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5 Speech Summarisation Transcribed speech usually includes not only redundant information such as disfluencies, filled pauses, repetitions, repairs and word fragments, but also irrelevant information caused by recognition errors. Therefore, especially for spontaneous speech, practical applications using speech recognition require a process of speech summarisation which removes redundant and irrelevant in- Speech Recognition Technology in Multimodal/Ubiquitous Environments 31 formation and extracts relatively important information corresponding to the users' requirements.

Buhler, D. and Minker, W. (2004). A reasoning component for informationseeking and planning dialogues. , editors, Spoken Multimodal Human-Computer Dialogue in Mobile Environments. Kluwer Academic Publishers, Dordrecht, The Netherlands, (this volume). Furui, S. (2004). Speech recognition technology in multimodal/ubiquitous computing environments. , editors, Spoken Multimodal Human-Computer Dialogue in Mobile Environments. Kluwer Academic Publishers, Dordrecht, The Netherlands, (this volume). Macherey, K.

Therefore, speech recognition systems are expected to play important roles in the ubiquitous/wearable computing environment (Furui, 2000b). The field of automatic speech recognition has witnessed a number of significant advances in the past 5-10 years, spurred on by advances in signal processing, algorithms, computational architectures, and hardware. These advances include the widespread adoption of a statistical pattern recognition paradigm, a data-driven approach which makes use of a rich set of speech utterances from a large population of speakers, the use of stochastic-based acoustic and language modelling, and the use of dynamic programming-based search methods (Juang and Furui, 2000; Rabiner and Juang, 1993; Furui, 2001; Furui, 2000a).

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