International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 135 - Issue 6 |
Published: February 2016 |
Authors: Sheena Christabel Pravin, Samyuktha Sundar, Krithika Aravindan |
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Sheena Christabel Pravin, Samyuktha Sundar, Krithika Aravindan . Feature Extraction from Non-Audible Murmur (NAM) for the Vocally Handicapped using Wavelet Transform. International Journal of Computer Applications. 135, 6 (February 2016), 29-32. DOI=10.5120/ijca2016908388
@article{ 10.5120/ijca2016908388, author = { Sheena Christabel Pravin,Samyuktha Sundar,Krithika Aravindan }, title = { Feature Extraction from Non-Audible Murmur (NAM) for the Vocally Handicapped using Wavelet Transform }, journal = { International Journal of Computer Applications }, year = { 2016 }, volume = { 135 }, number = { 6 }, pages = { 29-32 }, doi = { 10.5120/ijca2016908388 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2016 %A Sheena Christabel Pravin %A Samyuktha Sundar %A Krithika Aravindan %T Feature Extraction from Non-Audible Murmur (NAM) for the Vocally Handicapped using Wavelet Transform%T %J International Journal of Computer Applications %V 135 %N 6 %P 29-32 %R 10.5120/ijca2016908388 %I Foundation of Computer Science (FCS), NY, USA
Non audible murmur is a body conducted silent speech through which the vocally handicapped can communicate. We propose a method of acquisition of Non Audible Murmur (NAM), (i.e., inaudible speech produced without vibrations of the vocal folds) from the vocally handicapped using the MEMS accelerometer, followed by its de-noising and Statistical Feature Extraction. The murmur is acquired by placing the sensor bonded to the surface of the skin over the soft-cartilage bone behind the ear. The resulting electrical signal is de-noised using Discrete Wavelet Transform (DWT). Statistical Features are extracted from the detailed co-efficients of the de-noised murmur.