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

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