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 SYLLABLE DETECTION AND SEGMENTATION USING TEMPORAL ...
based approach) than a system based purely on phonetic segments [10][15][16]. In view of the above, we believe that segmentation of the acoustic signal into syllabic segments is an important stage in the development of a syllable-centric ASR system. 2. TEMPORAL FLOW MODEL We perform syllabic segmentation using a neural network archi-
Insertion reduction in speech segmentation using neural ...
Statistical approach with non-fixed overlapping window size is able to make good identification of discontinuity in speech signal without further knowledge upon the phonetic sequence. This however, leads to increase number of insertion and thus increase confusion in recognition. This paper present a fusion between statistical and connectionist approach namely divergence algorithm and MLP ......
ACCEPTED TO THE IEEE TRANSACTIONS ON AUDIO, SPEECH, AND ...
perform full-coverage segmentation of the data into a sequence of words. However, these models generally take phonemic or phonetic strings as input, rather than continuous speech. Early word segmentation approaches using phonemic input include those based on transition probabilities [15], neural net-works [16] and probabilistic models [17].
Isolated word recognition using modular recurrent neural ...
Sixty repetitions of each digit were recorded by five male speakers, 12 each, in a moderately quiet room. The speech data are divided into groups A and B, each containing six data sets. Two independent experiments are carried out by using one group of data for training and the other for testing.
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