Speech act identification using an ontology-based partial pattern tree

Chung Hsien Wu, Jui Feng Yeh, Ming Jun Chen

Research output: Contribution to conferencePaperpeer-review

1 Citation (Scopus)

Abstract

This paper presents an ontology-based partial pattern tree to identify the speech act in a spoken dialogue system. This study first extracts the key words/concepts in an application domain using latent semantic analysis (LSA). A partial pattern tree is used to deal with the ill-formed sentence problem in a spoken dialogue system. Concept expansion based on domain ontology is adopted to improve system performance. For performance evaluation, a medical dialogue system with multiple services, including registration information, clinic information and FAQ information, is implemented. Four performance measures were separately used for evaluation. The speech act identification rate achieves 86.2%. A Task Success Rate of 77% is obtained. The contextual appropriateness of the system response is 78.5%. Finally, the correct rate for FAQ retrieval is 82% with an improvement of 15% in comparison with the keyword-based vector space model. The results show the proposed ontology-based partial pattern tree is effective for dialogue management.

Original languageEnglish
Pages2157-2160
Number of pages4
Publication statusPublished - 2004 Jan 1
Event8th International Conference on Spoken Language Processing, ICSLP 2004 - Jeju, Jeju Island, Korea, Republic of
Duration: 2004 Oct 42004 Oct 8

Other

Other8th International Conference on Spoken Language Processing, ICSLP 2004
CountryKorea, Republic of
CityJeju, Jeju Island
Period04-10-0404-10-08

All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Linguistics and Language

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