i) 2016-Scopus Open Access (PDF)

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    GRAPH CUT BASED SEGMENTATION METHOD FOR TAMIL CONTINUOUS SPEECH
    (Springer Link, 2016) Laxmi Sree, B R; Vijaya, M S
    Automatic segmentation of continuous speech plays an important role in building promising acoustic models for a standard continuous speech recognition system. This needs a lot of segmented data which is rarely available for many languages. As there are no industry standard speech segmentation tools for Indian languages like Tamil, there arises a need to work on Tamil speech segmentation. Here, a segmentation algorithm that is based on Graph cut is proposed for automatic phonetic level segmentation of continuous speech. Using graph cut for speech segmentation allows viewing speech globally rather locally which helps in segmentation of vocabulary, speaker independent speech. The input speech is represented as a graph and the proposed algorithm is applied on it. Experiments on the speech database comprising utterances of various speakers shows the proposed method outperforms the existing methods Blind Segmentation using Non-Linear Filtering and Non-Uniform Segmentation using Discrete Wavelet Transform.