Title :
New perspectives on spoken language understanding: Does machine need to fully understand speech?
Author :
Kawahara, Tatsuya
Author_Institution :
ACCMS, Kyoto Univ., Kyoto, Japan
fDate :
Nov. 13 2009-Dec. 17 2009
Abstract :
Spoken language understanding (SLU) has been traditionally formulated to extract meanings or concepts of user utterances in the context of human-machine dialogue. With the broadened coverage of spoken language processing, the tasks and methodologies of SLU have been changed accordingly. The back-end of spoken dialogue systems now consist of not only relational databases (RDB) but also general documents, incorporating information retrieval (IR) and question-answering (QA) techniques. This paradigm shift and the author´s approaches are reviewed. SLU is also being designed to cover human-human dialogues and multi-party conversations. Major approaches to ¿understand¿ human-human speech communication and a new approach based on the lister´s reactions are reviewed. As a whole, these trends are apparently not oriented for full understanding of spoken language, but for robust extraction of clue information.
Keywords :
human computer interaction; information retrieval; interactive systems; speech recognition; automatic speech recognition; human-human dialogues; human-human speech communication; human-machine dialogue; information retrieval; multiparty conversations; question answering techniques; spoken dialogue systems; spoken language processing; spoken language understanding; Automatic speech recognition; Data mining; Error analysis; Information retrieval; Intelligent agent; Man machine systems; Natural languages; Oral communication; Relational databases; Robustness;
Conference_Titel :
Automatic Speech Recognition & Understanding, 2009. ASRU 2009. IEEE Workshop on
Conference_Location :
Merano
Print_ISBN :
978-1-4244-5478-5
Electronic_ISBN :
978-1-4244-5479-2
DOI :
10.1109/ASRU.2009.5373502