Template based speech enhancement of disordered speech
correlation coefficient; differently abled; Directly Radiated EL Noise (DREL); disordered speech; Electrolarynx (EL); F0 contour; Fundamental frequency - Pitch; K-measns algorithm; laryngectomy K-NN algrorithm; Larynx disorder; spectral subtraction; speech enhancement; speech intelligibility; speech naturalness; speech processing; Template matching algorithm
In this paper, we have taken Electro-Larynx (EL) speech and have improved the speech quality, electro-larynx speech was improved in terms of naturalness and intelligibility by introducing variations in the F0-contour and template matching with correlation coefficient. Initially, we introduced two different speech signals, the first speech signal introduced was healthy speech signal and the second speech signal introduced was disordered speech signal. Here, the second speech signal, the disordered speech is taken as the EL speech. The fundamental frequency or pitch was extracted first from the two inputed speech signals, then the contour of each fundamental frequency was extracted from the two input speech signals. Using these extracted features of fundamental frequency the gender classification by K-means algorithm was instigated. The same process was implemented with F0 contour features which was extracted using K-NN algorithm. EL speech contains directly radiated electrolarynx noise (DREL). The noise was filtered out using spectral subtraction algorithm. Once DREL noise is removed from EL speech, the quality of the speech was greatly improved. Then EL enhanced speech signal is compared and mapped with healthy speech signal using template matching algorithm with the help of correlation coefficient, this improves the overall quality, that is the naturalness and intelligibity of the introduced disordered speech signal. This technique helps solve the major problem of speech faced by differently abled persons with larynx disorder. 2016 IEEE.
Proceedings of IEEE International Conference on Circuit, Power and Computing Technologies, ICCPCT 2016
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ICCPCT.2016.7530254 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992124420&doi=10.1109%2fICCPCT.2016.7530254&partnerID=40&md5=771c8c03a7a4c853d9120b9470f254e5
Poornima K.A., Department of ECE, Christ University, Faculty of Engineering, Bangalore, India; Inbanila K., Department of ECE, Christ University, Faculty of Engineering, Bangalore, India