Abstract
An informative and comprehensive overview of the state-of-the-art in natural language generation (NLG) for interactive systems, this guide serves to introduce graduate students and new researchers to the field of natural language processing and artificial intelligence, while inspiring them with ideas for future research. Detailing the techniques and challenges of NLG for interactive applications, it focuses on the research into systems that model collaborativity and uncertainty, are capable of being scaled incrementally, and can engage with the user effectively. A range of real-world case studies is also included. The book and the accompanying website feature a comprehensive bibliography, and refer the reader to corpora, data, software and other resources for pursuing research on natural language generation and interactive systems, including dialog systems, multimodal interfaces and assistive technologies. It is an ideal resource for students and researchers in computational linguistics, natural language processing and related fields.
Description of state of the art brings readers up to speed on the techniques and challenges of the field
A comprehensive bibliography enables researchers and practitioners to find related work in this area
The accompanying website allows researchers and practitioners to find and use data sets and code
Description of state of the art brings readers up to speed on the techniques and challenges of the field
A comprehensive bibliography enables researchers and practitioners to find related work in this area
The accompanying website allows researchers and practitioners to find and use data sets and code
Original language | English |
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Title of host publication | Natural Language Generation in Interactive Systems |
Editors | Amanda Stent, Srinivas Bangalore |
Place of Publication | Cambridge |
Publisher | Cambridge University Press |
Number of pages | 26 |
ISBN (Electronic) | 9781139898287 |
ISBN (Print) | 9781107010024 |
DOIs | |
Publication status | Published - 1 Jul 2014 |
Keywords
- Referring expressions
- Natural language generation
- Computational linguistics
- Alignment
- Dialogue