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Data-Driven Methods for Adaptive Spoken Dialogue Systems

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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.
Data-Driven Methods for Adaptive Spoken Dialogue Systems: Computational Learning for Conversational Interfaces (Paperback)

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

005.74 OLI d

Penerbit

New York : Springer International Publishing., 2012

Deskripsi Fisik

ix + 177 hlm.; 23 cm

Bahasa

English

ISBN/ISSN

9781461448020

Klasifikasi

005.74

Tipe Isi

text

Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

Pemrogaman

Info Detail Spesifik

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Pernyataan Tanggungjawab

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