Exploiting Dynamic Passage Retrieval for Spoken Question Recognition and Context Processing towards Speech-driven Information Access Dialogue

Tomoyosi Akiba

Abstract
Speech interfaces and dialogue processing abilities have promise for improving the utility of open-domain question answering (QA).We propose a novel method of resolving disambiguation problems arisen in those speech and dialogue enhanced QA tasks. The proposed method exploits passage retrieval, which is one of main components common in many QA systems. The basic idea of the method is that the similarity with some passage in the target documents can be used to select the appropriate question from the candidates. In this paper, we applied the method to solve two subtasks of QA, which are (1) N-best rescoring of LVCSR outputs, which selects a most appropriate candidate as a question sentence, in speech-driven QA (SDQA) task and (2) context processing, which compose a complete question sentence from a submitted incomplete one by using the elements appeared in the dialogue context, in information access dialogue (IAD) task. For both tasks, a dynamic passage retrieval is introduced to further improve the performance. The experimental results showed that the proposed method is quite effective in order to improve the performance of QA in both two tasks.
Anthology ID:
L06-1393
Volume:
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
Month:
May
Year:
2006
Address:
Genoa, Italy
Venue:
LREC
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Publisher:
European Language Resources Association (ELRA)
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URL:
http://www.lrec-conf.org/proceedings/lrec2006/pdf/637_pdf.pdf
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Cite (ACL):
Tomoyosi Akiba. 2006. Exploiting Dynamic Passage Retrieval for Spoken Question Recognition and Context Processing towards Speech-driven Information Access Dialogue. In Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06), Genoa, Italy. European Language Resources Association (ELRA).
Cite (Informal):
Exploiting Dynamic Passage Retrieval for Spoken Question Recognition and Context Processing towards Speech-driven Information Access Dialogue (Akiba, LREC 2006)
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http://www.lrec-conf.org/proceedings/lrec2006/pdf/637_pdf.pdf
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