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The focus of this paper is two-fold: to develop a knowledge-based robust syllable segmentation algorithm and to establish the importance of accurate segmentation in both the training and testing phases of a speech recognition system. A robust segmentation algorithm for segmenting the speech signal into syllables is first developed. This uses a non-statistical technique that is based on Group Delay (GD) segmentation and Vowel Onset Point(VOP) detection. The transcription corresponding to the utterance is syllabified using rules. This produces an annotation for the train data. The annotated train data is then used to train a syllable-based speech recognition system.
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