Data-Driven Methods for Adaptive Spoken Dialogue Systems : Computational Learning for Conversational Interfaces PDF
Edited by Oliver Lemon, Olivier Pietquin
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Description
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.
Information
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Download - Immediately Available
- Format:PDF
- Publisher:Springer New York
- Publication Date:01/01/1900
- Category:
- ISBN:9781461448037
Information
-
Download - Immediately Available
- Format:PDF
- Publisher:Springer New York
- Publication Date:01/01/1900
- Category:
- ISBN:9781461448037
