Paper Title :A Novel Automatic Voice Recognition System using a Graph-Based Clustering Algorithm
Author :Tudor Barbu
Article Citation :Tudor Barbu ,
(2022 ) " A Novel Automatic Voice Recognition System using a Graph-Based Clustering Algorithm " ,
International Journal of Advance Computational Engineering and Networking (IJACEN) ,
pp. 1-6,
Volume-10,Issue-9
Abstract : Abstract – Weconsiderhereanovel automatic unsupervised speech-dependent speaker recognition technique. The proposed approach clusters a set of speech sequences in voice classes corresponding to the generating speakers, whose number is unknown. The speech feature vectors of these utterances are constructed by using the mel-cepstral analysis. Then, an automatic unsupervised classification is performed on the obtained feature vectors. A graph theory-based vocal feature vector clustering method is proposed for this task. It groups the vocal sequences in a proper number of speaker-classes. Experiments and method comparison illustrating the effectiveness of the proposed technique are also described in this research paper.
Keywords - Unsupervised Speech-Dependent Voice Recognition; Mel-Cepstral Analysis; Speech Feature Extraction; Graph Clustering; Normalized-Cut Algorithm.
Type : Research paper
Published : Volume-10,Issue-9
DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-19038
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Copyright: © Institute of Research and Journals
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Published on 2022-12-21 |
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