JPR_V3_N4_RP4
An Analysis of Speech Signal for Multiple Languages through Spectrum Analysis
Pooja Yadav
Vinay Kumar Jain
Journal on Pattern Recognition
2350-112X
3
4
22
27
Speech Recognition, Computational Efficiency, Speaker Recognition MFCC, LPCC
The listeners outperform Automatic speech recognition structures in each and every speech reputation task. Modern excessive-tech automated speech recognition systems carry out very well in environments, wherein the speech indicators are reasonably easy. In maximum of the instances, popularity with the aid of machines degrades dramatically with mild adjustment in speech signals or talking environment, for this reason complicated algorithms are used to symbolize this unpredictability. So, the speech can be easily identified. Speech generation gives many possibilities for private identity, which is practical and non-intrusive. Besides that, speech era offers the capability to verify the identity of a person remotely over long distance by using an ordinary phone. In this paper, the authors have proposed a technique to apprehend any words or speech thru the spectrogram analysis. This technique is used to look at the ideas of speaker reputation in multiple languages and apprehend its uses in identification and verification systems and to assess the recognition capability of various voice functions and parameters. To find out the technique, this is appropriate for Automatic Speaker Recognition systems in phrases of reliability and computational efficiency.
December 2016 - February 2017
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