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Feature Extraction from Non-Audible Murmur (NAM) for the Vocally Handicapped using Wavelet Transform
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 135 - Number 6 |
| Year of Publication: 2016 |
| Authors: Sheena Christabel Pravin, Samyuktha Sundar, Krithika Aravindan |
10.5120/ijca2016908388
|
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
Abstract
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.
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