English Sentence Recognition Based on HMM and Clustering
نویسندگان
چکیده
منابع مشابه
English Sentence Recognition Based on HMM and Clustering
For English sentences with a large amount of feature data and complex pronunciation changes contrast to words, there are more problems existing in Hidden Markov Model (HMM), such as the computational complexity of the Viterbi algorithm and mixed Gaussian distribution probability. This article explores the segment-mean algorithm for dimensionality reduction of speech feature parameters, the clus...
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The paper presents a Segment-Mean method for reducing the dimension of the speech feature parameters. K-Means function is used to group the speech feature parameters whose dimension has been reduced. And then the speech samples are classified into different clusters according to their features. It proposes a cross-group training algorithm for the speech feature parameters clustering which impro...
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Aiming at the problem that the identification precision in intonation evaluation and analysis of English sentences is not high, this paper proposes a method of English sentences on the basis of ontology graph clustering evaluation. First, we study the ontology-graph evaluation model of English sentences, conduct objective evaluation to English sentences based on the fundamental framework of KL ...
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ژورنال
عنوان ژورنال: American Journal of Computational Mathematics
سال: 2013
ISSN: 2161-1203,2161-1211
DOI: 10.4236/ajcm.2013.31005