Essence Vector-Based Query Modeling for Spoken Document Retrieval

Kuan Yu Chen, Shih Hung Liu, Berlin Chen, Hsin Min Wang

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

1 Citation (Scopus)

Abstract

Spoken document retrieval (SDR) has become a prominently required application since unprecedented volumes of multimedia data along with speech have become available in our daily life. As far as we are aware, there has been relatively less work in launching unsupervised paragraph embedding methods and investigating the effectiveness of these methods on the SDR task. This paper first presents a novel paragraph embedding method, named the essence vector (EV) model, which aims at inferring a representation for a given paragraph by encapsulating the most representative information from the paragraph and excluding the general background information at the same time. On top of the EV model, we develop three query language modeling mechanisms to improve the retrieval performance. A series of empirical SDR experiments conducted on two benchmark collections demonstrate the good efficacy of the proposed framework, compared to several existing strong baseline systems.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6274-6278
Number of pages5
ISBN (Print)9781538646588
DOIs
Publication statusPublished - 2018 Sep 10
Event2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Calgary, Canada
Duration: 2018 Apr 152018 Apr 20

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2018-April
ISSN (Print)1520-6149

Conference

Conference2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
CountryCanada
CityCalgary
Period18/4/1518/4/20

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Keywords

  • Essence vector
  • Query modeling
  • Retrieval
  • Spoken document

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Chen, K. Y., Liu, S. H., Chen, B., & Wang, H. M. (2018). Essence Vector-Based Query Modeling for Spoken Document Retrieval. In 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings (pp. 6274-6278). [8461687] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2018-April). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2018.8461687