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portada data-driven methods for adaptive spoken dialogue systems: computational learning for conversational interfaces
Type
Physical Book
Illustrated by
Publisher
Author
Year
2012
Language
English
Pages
178
Format
Hardcover
Dimensions
23.6x15.5x1.5 cm
Weight
0.50 kg.
ISBN
1461448026
ISBN13
9781461448020
Categories

data-driven methods for adaptive spoken dialogue systems: computational learning for conversational interfaces

Oliver Lemon (Illustrated by) · Olivier Pietquin (Illustrated by) · Springer · Hardcover

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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