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Comparison and Analysis of NAM and Acoustic Speech Using Wavelet Transform
RADHIKA.R, VANITHA LAKSHMI.M, AADITYA VELAVA.V.A
PG Scholar, Dept of PG studies in Engineering, S.A Engineering College, Chennai, India Assistant professor, Dept of PG studies in Engineering, S.A Engineering College, Chennai, India PG Scholar, Dept of PG studies in Engineering, S.A Engineering College, Chennai, India
Abstract: Non-Audible Murmur (NAM) is a very quietly uttered speech received through the body tissue with the use of special acoustic sensors (i.e., NAM microphone) attached behind the talker’s ear. Analysis of NAM speech has been made only using HMM (Hidden Markov Model) and GMM (Gaussian Markov Model). In this paper, study of analysing acoustic speech and NAM speech will be made using Wavelet transform. Since, wavelets have the great advantage of being able to separate the fine details in a signal. It allows complex information such as music, speech, and patterns to be decomposed into elementary forms at different positions and subsequently reconstruct it with high precision. Upon analysing the Normal speech, NAM speech will also be analysed using the same wavelet transform. The accuracy of words obtained from the two methods will be compared to determine the efficiency of using Wavelet transform in recognizing NAM speech.
Keywords: NAM (Non-Audible Murmur), HMM (Hidden Markov Model), GMM (Gaussian Markov Model), NAM Microphone
Keywords: NAM (Non-Audible Murmur), HMM (Hidden Markov Model), GMM (Gaussian Markov Model), NAM Microphone
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This work is licensed under a Creative Commons Attribution 4.0 International License.How to Cite:
[1] RADHIKA.R, VANITHA LAKSHMI.M, AADITYA VELAVA.V.A, “Comparison and Analysis of NAM and Acoustic Speech Using Wavelet Transform,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE)