Effective pseudo-relevance feedback for spoken document retrieval

Yi Wen Chen, Kuan Yu Chen, Hsin Min Wang, Berlin Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

With the exponential proliferation of multimedia associated with spoken documents, research on spoken document retrieval (SDR) has emerged and attracted much attention in the past two decades. Apart from much effort devoted to developing robust indexing and modeling techniques for representing spoken documents, a recent line of thought targets at the improvement of query modeling for better reflecting the user's information need. Pseudo-relevance feedback is by far the most commonly-used paradigm for query reformulation, which assumes that a small amount of top-ranked feedback documents obtained from the initial round of retrieval are relevant and can be utilized for this purpose. Nevertheless, simply taking all of the top-ranked feedback documents obtained from the initial retrieval for query modeling (reformulation) does not always work well, especially when the top-ranked documents contain much redundant or non-relevant information. In the view of this, we explore in this paper an interesting problem of how to effectively glean useful cues from the top-ranked documents so as to achieve more accurate query modeling. To do this, different kinds of information cues are considered and integrated into the process of feedback document selection so as to improve query effectiveness. Experiments conducted on the TDT (Topic Detection and Tracking) task show the advantages of our retrieval methods for SDR.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages8535-8539
Number of pages5
DOIs
Publication statusPublished - 2013 Oct 18
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: 2013 May 262013 May 31

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
CountryCanada
CityVancouver, BC
Period13/5/2613/5/31

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Experiments

Keywords

  • Kullback-Leibler (KL)-divergence
  • Spoken document retrieval
  • pseudo-relevance feedback
  • query modeling

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Chen, Y. W., Chen, K. Y., Wang, H. M., & Chen, B. (2013). Effective pseudo-relevance feedback for spoken document retrieval. In 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings (pp. 8535-8539). [6639331] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2013.6639331

Effective pseudo-relevance feedback for spoken document retrieval. / Chen, Yi Wen; Chen, Kuan Yu; Wang, Hsin Min; Chen, Berlin.

2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings. 2013. p. 8535-8539 6639331 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chen, YW, Chen, KY, Wang, HM & Chen, B 2013, Effective pseudo-relevance feedback for spoken document retrieval. in 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings., 6639331, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, pp. 8535-8539, 2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013, Vancouver, BC, Canada, 13/5/26. https://doi.org/10.1109/ICASSP.2013.6639331
Chen YW, Chen KY, Wang HM, Chen B. Effective pseudo-relevance feedback for spoken document retrieval. In 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings. 2013. p. 8535-8539. 6639331. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2013.6639331
Chen, Yi Wen ; Chen, Kuan Yu ; Wang, Hsin Min ; Chen, Berlin. / Effective pseudo-relevance feedback for spoken document retrieval. 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings. 2013. pp. 8535-8539 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).
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