Title :
Improving Bone-Conducted Speech Quality via Neural Network
Author :
Shimamura, Tetsuya ; Mamiya, J. ; Tamiya, Toshiki
Author_Institution :
Dept. of Inf. & Comput. Sci., Saitama Univ.
Abstract :
The quality of bone-conducted speech is low, but bone-conducted speech itself is not affected by noise. In this paper, we take into account such properties of bone-conducted speech, and derive a reconstruction filter to improve the quality of bone-conducted speech. The reconstruction filter is designed by learning a neural network on the basis of the bone-conducted speech and normal speech obtained from a speaker. Experimental results show that the reconstructed speech signal has better quality than the bone-conducted speech signal
Keywords :
filtering theory; neural nets; speech processing; bone-conducted speech quality; neural network; reconstruction filter; Bones; Filtering; Filters; Frequency; Neural networks; Signal design; Signal processing; Speech enhancement; Speech processing; Working environment noise; bone conduction; neural network; reconstruction filter; speech quality;
Conference_Titel :
Signal Processing and Information Technology, 2006 IEEE International Symposium on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9753-3
Electronic_ISBN :
0-7803-9754-1
DOI :
10.1109/ISSPIT.2006.270876
