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portada Data-Driven Methods for Adaptive Spoken Dialogue Systems: Computational Learning for Conversational Interfaces
Type
Physical Book
Publisher
Author
Language
English
Pages
178
Format
Paperback
Dimensions
23.4 x 15.6 x 1.0 cm
Weight
0.27 kg.
ISBN13
9781489992833
Categories

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

Lemon, Oliver ; Pietquin, Olivier (Author) · Springer · Paperback

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

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Synopsis "Data-Driven Methods for Adaptive Spoken Dialogue Systems: Computational Learning for Conversational Interfaces"

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. 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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