Volume 12, Issue 1, July 2015, Pages 33–61
Md. Shahadat Hossain1, Ariful Islam2, and Md. Rafiqul Islam3
1 Mathematics Discipline, Science Engineering and Technology School, Khulna University, Khulna-9208, Bangladesh
2 Mathematics Discipline, Science Engineering and Technology School, Khulna University, Khulna-9208, Bangladesh
3 Mathematics Discipline, Science Engineering and Technology School, Khulna University, Khulna-9208, Bangladesh
Original language: English
Copyright © 2015 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Wavelet has wide range of use in the present scientific universe. At present using wavelet through MATLAB different types of tasks are done. For instance biometric recognition (fingerprint recognition, voice recognition, iris recognition, face recognition, pattern recognition and signature recognition), signal processing, human voice activity detection etc. are done using wavelet and wavelet transform. Among these here I have discussed about "Human Voice Activity Detection". At first a human voice is taken as the input sound to MATLAB command window using a good headphone for a few second. Then the sound taken as input give a graphical representation that is saved for future activities. After that using the wavelet toolbox of MATLAB the image of the input sound is taken for analyzing it. Using discrete wavelet transform the image is analyzed. During this analysis a "10 level wavelet" tree is generated by Haar wavelet with 10 decomposition level. At the same time the original signal is reconstructed. At the first time six different human voice activities of the same persons are analyzed. The Norm and the SNR (Signal to Noise Ratio) are counted. The data of the SNR are counted in decibel (db.) unit. Also the bit rates of the three different voice are counted. In this way total 18 different experiments are done for the different five persons where except the first person for all the person three experiments are dine.. The numerical data of the experiments are shown as graphical representation as well as in histogram analysis. In this process the whole experiments are done for the activity detection of human voice.
Author Keywords: Wavelet, SNR, Bit rate, Human voice, Histogram.
Md. Shahadat Hossain1, Ariful Islam2, and Md. Rafiqul Islam3
1 Mathematics Discipline, Science Engineering and Technology School, Khulna University, Khulna-9208, Bangladesh
2 Mathematics Discipline, Science Engineering and Technology School, Khulna University, Khulna-9208, Bangladesh
3 Mathematics Discipline, Science Engineering and Technology School, Khulna University, Khulna-9208, Bangladesh
Original language: English
Copyright © 2015 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Wavelet has wide range of use in the present scientific universe. At present using wavelet through MATLAB different types of tasks are done. For instance biometric recognition (fingerprint recognition, voice recognition, iris recognition, face recognition, pattern recognition and signature recognition), signal processing, human voice activity detection etc. are done using wavelet and wavelet transform. Among these here I have discussed about "Human Voice Activity Detection". At first a human voice is taken as the input sound to MATLAB command window using a good headphone for a few second. Then the sound taken as input give a graphical representation that is saved for future activities. After that using the wavelet toolbox of MATLAB the image of the input sound is taken for analyzing it. Using discrete wavelet transform the image is analyzed. During this analysis a "10 level wavelet" tree is generated by Haar wavelet with 10 decomposition level. At the same time the original signal is reconstructed. At the first time six different human voice activities of the same persons are analyzed. The Norm and the SNR (Signal to Noise Ratio) are counted. The data of the SNR are counted in decibel (db.) unit. Also the bit rates of the three different voice are counted. In this way total 18 different experiments are done for the different five persons where except the first person for all the person three experiments are dine.. The numerical data of the experiments are shown as graphical representation as well as in histogram analysis. In this process the whole experiments are done for the activity detection of human voice.
Author Keywords: Wavelet, SNR, Bit rate, Human voice, Histogram.
How to Cite this Article
Md. Shahadat Hossain, Ariful Islam, and Md. Rafiqul Islam, “HUMAN VOICE ACTIVITY DETECTION USING WAVELET,” International Journal of Innovation and Applied Studies, vol. 12, no. 1, pp. 33–61, July 2015.
