Feature Extraction from Non-Audible Murmur (NAM) for the Vocally Handicapped using Wavelet Transform {tag} {/tag} 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 {bibtex}2016908388.bib{/bibtex} 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. References 1. B. Denby, T. Schultz, K. Honda, T. Hueber, M.Gilbert, and S.Brumberg. Silent speech interfaces, Speech Communication, Vol. 52, No. 4, pp. 270-287, 2010. 1 / 3