Handbook of Multimodal and Spoken Dialogue Systems

This article presents a bilingual ontology-based dialog system with multiple services. An ontology-alignment algorithm is proposed to integrate ontologies of different languages for cross-language applications. A domainspecific ontology is further extracted from the bilingual ontology using an island-driven algorithm and a domain corpus. This study extracts the semantic words/concepts using latent semantic analysis (LSA). Based on the extracted semantic words and the domain ontology, a partial pattern tree is constructed to model the speech act of a spoken utterance. The partial pattern tree is used to deal with the ill-formed sentence problem in a spokendialog system. Concept expansion based on domain ontology is also adopted to improve system performance. For performance evaluation, a medical dialog system with multiple services, including registration information, clinic information, and FAQ information, is implemented. Four performance measures were used separately for evaluation. The speech act identification rate was 86.2%. A task success rate of 77% was obtained. The contextual appropriateness of the system response was 78.5%. Finally, the rate for correct FAQ retrieval was 82%, an improvement of 15% over the keyword-based vectorspace model. The results show the proposed ontologybased speech-act identification is effective for dialog management.

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Handbook of Multimodal and Spoken Dialogue Systems

Abstract: with support from many colleagues around the world, in particular from Metin Erdogan,

Cited by 57 publications

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Ontology‐based speech act identification in a bilingual dialog system using partial pattern trees

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