A Hybrid Computational Model for Spoken Language Understanding

被引:0
作者
Huang, Guangpu [1 ]
Er, Meng Joo [1 ]
机构
[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore, Singapore
来源
11TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV 2010) | 2010年
关键词
Human-computer interaction; spoken language understanding; speech recognition; natural language understanding; HIDDEN MARKOV-MODELS; SPEECH RECOGNITION;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:2078 / 2083
页数:6
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