Speech and Non-Speech Identification and Classification using KNN Algorithm

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Bibliographic Details
Title: Speech and Non-Speech Identification and Classification using KNN Algorithm
Authors: Priya, T. Lakshmi rmtlpriya1208@gmail.com, Raajan, N.R.1, Raju, N.1, Preethi, P.1, Mathini, S.1
Source: Procedia Engineering. Sep2012, Vol. 38, p952-958. 7p.
Subjects: Speech perception, Nearest neighbor analysis (Statistics), Signal processing, Algorithms, Performance evaluation, Signal-to-noise ratio
Abstract: Abstract: Speech and non-speech identification along with its classification method that need to be improved in the endpoint detection for speech in noisy environments. The proposed method uses few features to increase the robustness in various noisy environments, and the classification used here KNN technique is applied to effectively combine these multiple features for classification of each speech signal. We evaluate the performance of the proposed method by conducting speech and non-speech classification experiments on noisy speech. We also investigate the importance of various features on speech and non-speech classification in noisy environments and by using this KNN algorithm to obtaining 80% accuracy. [Copyright &y& Elsevier]
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Database: Engineering Source
Description
Abstract:Abstract: Speech and non-speech identification along with its classification method that need to be improved in the endpoint detection for speech in noisy environments. The proposed method uses few features to increase the robustness in various noisy environments, and the classification used here KNN technique is applied to effectively combine these multiple features for classification of each speech signal. We evaluate the performance of the proposed method by conducting speech and non-speech classification experiments on noisy speech. We also investigate the importance of various features on speech and non-speech classification in noisy environments and by using this KNN algorithm to obtaining 80% accuracy. [Copyright &y& Elsevier]
ISSN:18777058
DOI:10.1016/j.proeng.2012.06.120