Stock image for illustration purposes only - book cover, edition or condition may vary.
Data-Driven Methods for Adaptive Spoken Dialogue Systems: Computational Learning for Conversational Interfaces
. Ed(S): Lemon, Oliver; Pietquin, Olivier
€ 118.63
FREE Delivery in Ireland
Description for Data-Driven Methods for Adaptive Spoken Dialogue Systems: Computational Learning for Conversational Interfaces
paperback. Based on dialogue systems freely available for academic use, this book covers state-of-the-art research in data-driven, machine-learning approaches to developing spoken conversational interfaces, collating the data from the EU's groundbreaking CLASSIC project. Editor(s): Lemon, Oliver; Pietquin, Olivier. Num Pages: 178 pages, 23 black & white tables, biography. BIC Classification: CFX; TTBM; UGK; UMB; UYZG. Category: (G) General (US: Trade). Dimension: 235 x 155 x 10. Weight in Grams: 297.
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 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.
Product Details
Format
Paperback
Publication date
2014
Publisher
Springer United States
Number of pages
178
Condition
New
Number of Pages
178
Place of Publication
New York, United States
ISBN
9781489992833
SKU
V9781489992833
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About . Ed(S): Lemon, Oliver; Pietquin, Olivier
Oliver Lemon is a Reader and head of the Interaction Lab in the school of Mathematical and Computer Sciences at Heriot Watt University, Edinburgh. Dr. Lemon is currently serving as the Program Chair for SIGDial 2010 and as a member of the Program Committee of INLG 2010. He is also on the Editorial Board of the new journal "Dialogue & ... Read more
Reviews for Data-Driven Methods for Adaptive Spoken Dialogue Systems: Computational Learning for Conversational Interfaces