Natural Language Generation in Interactive Systems

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.

1. Communicative intentions and natural language generation Nate Blaylock; 2. Pursuing and demonstrating understanding in dialogue David DeVault and Matthew Stone; 3. Dialogue and compound contributions Matthew Purver, Julian Hough and Eleni Gregoromichelaki; 4. Eye tracking for the online evaluation of prosody in speech synthesis Michael White, Rajakrishnan Rajkumar, Kiwako Ito and Shari R. Speer; 5. Referability Kees van Deemter; 6. Referring expression generation in interaction: a graph-based perspective Emiel Krahmer, Martijn Goudbeek and Mariet Theune; 7. Reinforcement learning approaches to natural language generation in interactive systems Oliver Lemony, Srini Janarthanam and Verena Rieser; 8. A joint learning approach for situated language generation Nina Dethlefs and Heriberto Cuayáhuitl; 9. Data-driven methods for linguistic style control Francois Mairesse; 10. Integration of cultural factors into the behavioural models of virtual characters Birgit Endrass and Elisabeth Andre; 11. Natural language generation for augmented and assistive technologies Nava Tintarev, Ehud Reiter and Annalu Waller; 12. Comparative evaluation and shared tasks for NLG in interactive systems Anja Belz and Helen Hastie.

Amanda Stent is a researcher at AT&T Labs – Research. Her areas of interest are at the intersection of dialog systems and natural language generation and include coreference, sentence planning, alignment in dialog, and applications of NLG to topics ranging from computer security to assistive technology. Dr Stent has authored over 70 research publications and holds several patents.
Srinivas Bangalore has been at AT&T Labs – Research since 1997 and has worked on many areas of natural language processing including spoken language translation, multimodal understanding, language generation and question-answering. He has co-edited a book, Supertagging, authored over 100 research publications, and holds 45 patents in these areas. He has been awarded the AT&T Outstanding Mentor Award and the AT&T Science and Technology Medal.