A hybrid computational model for spoken language understanding

Author

Huang, Guangpu ; Er, Meng Joo

Author_Institution

Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore

fYear

2010

fDate

7-10 Dec. 2010

Firstpage

2078

Lastpage

2083

Abstract

This paper shows that the integration of statistical and connectionist methods can greatly enhance human-computer interaction through speech. The research approach is inspired by recent advances in high performance automatic speech recognition (ASR) systems and neurocognitive researches of natural language understanding (NLU). And a modest hybrid computational model is proposed and implemented to achieve intelligent spoken language understanding (SLU) in an information retrieval system.

Keywords

cognitive systems; human computer interaction; information retrieval; natural language processing; speech recognition; statistical analysis; automatic speech recognition system; human computer interaction; hybrid computational model; information retrieval system; intelligent spoken language understanding; natural language understanding; neurocognitive research; statistical methods; Acoustics; Computational modeling; Hidden Markov models; Semantics; Speech; Speech recognition; Syntactics; Human-computer interaction; natural language understanding; speech recognition; spoken language understanding;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Automation Robotics & Vision (ICARCV), 2010 11th International Conference on

Conference_Location

Singapore

Print_ISBN

978-1-4244-7814-9

Type

conf

DOI

10.1109/ICARCV.2010.5707258

Filename

5707258