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    Word spotting in continuous speech using wavelet transform

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    Publication date
    2014
    Author
    Khan, W.
    Jiang, Ping
    Holton, David R.W.
    Keyword
    Speech; Wavelet transforms; Feature extraction; Time-frequency analysis; Acoustics
    Peer-Reviewed
    Yes
    
    Metadata
    Show full item record
    Abstract
    Word spotting in continuous speech is considered a challenging issue due to dynamic nature of speech. Literature contains a variety of novel techniques for the isolated word recognition and spotting. Most of these techniques are based on pattern recognition and similarity measures. This paper amalgamates the use of different techniques that includes wavelet transform, feature extraction and Euclidean distance. Based on the acoustic features, the proposed system is capable of identifying and localizing a target (test) word in a continuous speech of any length. Wavelet transform is used for the time-frequency representation and filtration of speech signal. Only high intensity frequency components are passed to feature extraction and matching process resulting robust performance in terms of matching as well as computational cost.
    URI
    http://hdl.handle.net/10454/10713
    Version
    No full-text in the repository
    Citation
    Khan W, Jiang P and Holton DRW (2014) Word spotting in continuous speech using wavelet transform. In: Proceedings of the IEEE International Conference on Electro/Information Technology (EIT). 5-7 Jun 2014, Milwaukee, WI, USA: 275-259.
    Link to publisher’s version
    https://doi.org/10.1109/EIT.2014.6871776
    Type
    Conference Paper
    Collections
    Engineering and Informatics Publications

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