Data-Driven Methods for Adaptive Spoken Dialogue Systems: Computational Learning for Conversational Interfaces Oliver Lemon

ISBN: 9781461448037

Published: January 1st 2012

Unknown Binding

183 pages


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Data-Driven Methods for Adaptive Spoken Dialogue Systems: Computational Learning for Conversational Interfaces  by  Oliver Lemon

Data-Driven Methods for Adaptive Spoken Dialogue Systems: Computational Learning for Conversational Interfaces by Oliver Lemon
January 1st 2012 | Unknown Binding | PDF, EPUB, FB2, DjVu, audiobook, mp3, ZIP | 183 pages | ISBN: 9781461448037 | 8.58 Mb

Data driven methods have long been used in Automatic Speech Recognition (ASR) and Text-To-Speech (TTS) synthesis and have more recently been introduced for dialogue management, spoken language understanding, and Natural Language Generation.

MachineMoreData driven methods have long been used in Automatic Speech Recognition (ASR) and Text-To-Speech (TTS) synthesis and have more recently been introduced for dialogue management, spoken language understanding, and Natural Language Generation. Machine learning is now present end-to-end in Spoken Dialogue Systems (SDS). However, these techniques require data collection and annotation campaigns, which can be time-consuming and expensive, as well as dataset expansion by simulation. In this book, we provide an overview of the current state of the field and of recent advances, with a specific focus on adaptivity.



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