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Keyword spotting based on the analysis of template matching distances

Conference Paper


Abstract


  • This paper presents a system for speaker

    independent keyword spotting (KWS) in continuous speech using

    a spoken example template. The approach, based on Dynamic

    Time Warping (DTW) for matching the template to a test

    utterance, does not require any modelling or training as required

    in alternative techniques such as the Hidden Markov Model

    (HMM). This is of particular relevance to applications such as

    detection of words that have not been adequately represented in

    a training database (e.g. searching for topical words that are

    emerging in society). Introduced is the use of the DTW distance

    histogram for automatic estimation of similarity thresholds for

    every keyword-utterance pair. Experiments conducted on a wide

    range of speech sentences and keywords show that when only a

    few examples of the keyword are available, the proposed system

    has higher recall ratio than a HMM-based approach.

Publication Date


  • 2011

Citation


  • M. S. Barakat, C. H. Ritz & D. A. Stirling, "Keyword spotting based on the analysis of template matching distances," in 5th International Conference on Signal Processing and Telecommunication Systems, ICSPCS'2011, 2011, pp. 1-6.

Scopus Eid


  • 2-s2.0-84857339613

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/1772

Start Page


  • 1

End Page


  • 6

Place Of Publication


  • http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=06140822

Abstract


  • This paper presents a system for speaker

    independent keyword spotting (KWS) in continuous speech using

    a spoken example template. The approach, based on Dynamic

    Time Warping (DTW) for matching the template to a test

    utterance, does not require any modelling or training as required

    in alternative techniques such as the Hidden Markov Model

    (HMM). This is of particular relevance to applications such as

    detection of words that have not been adequately represented in

    a training database (e.g. searching for topical words that are

    emerging in society). Introduced is the use of the DTW distance

    histogram for automatic estimation of similarity thresholds for

    every keyword-utterance pair. Experiments conducted on a wide

    range of speech sentences and keywords show that when only a

    few examples of the keyword are available, the proposed system

    has higher recall ratio than a HMM-based approach.

Publication Date


  • 2011

Citation


  • M. S. Barakat, C. H. Ritz & D. A. Stirling, "Keyword spotting based on the analysis of template matching distances," in 5th International Conference on Signal Processing and Telecommunication Systems, ICSPCS'2011, 2011, pp. 1-6.

Scopus Eid


  • 2-s2.0-84857339613

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/1772

Start Page


  • 1

End Page


  • 6

Place Of Publication


  • http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=06140822