DocumentCode
699181
Title
Audible (normal) speech and inaudible murmur recognition using NAM microphone
Author
Heracleous, Panikos ; Nakajima, Yoshitaka ; Akinobu Lee ; Saruwatari, Hiroshi ; Shikano, Kiyohiro
Author_Institution
Grad. Sch. of Inf. Sci., Nara Inst. of Sci. & Technol., Ikoma, Japan
fYear
2004
fDate
6-10 Sept. 2004
Firstpage
329
Lastpage
332
Abstract
In this paper, we present audible (normal) speech and inaudible murmur hidden Markov models based automatic speech recognition using NAM microphone. The NAM (Non-Audible Murmur) microphone is a special device, which can be used for capturing inaudible murmur speech. The device is based on the stethoscope, which is used in medical science. By attaching the NAM microphone behind the talker´s ear, we can receive very quietly uttered speech and perform automatic speech recognition in a conventional way. Privacy, robustness to environmental, and a useful tool for sound-impaired people noise belong to the advantages of the NAM microphone. Using adaptation techniques, we created hidden Markov models for inaudible speech and we performed automatic speech recognition. The achieved results are very promising, and prove the effectiveness of NAM microphone In this paper, we also introduce our work for recognizing normal speech using NAM microphone. The idea is to take advantage of noise robustness of NAM microphone. In our experiments, we achieved a 93.8% word accuracy in clean environment, and a 93.1% word accuracy in noisy environment. In this paper, we also introduce two techniques to intergrate inaudible murmur and audible speech recognition using NAM microphone. In both cases, we achieved a 92.1% word accuracy on average, which is a very promising result.
Keywords
hidden Markov models; microphones; speech recognition; NAM microphone; audible normal speech recognition; automatic speech recognition; inaudible murmur hidden Markov model; inaudible murmur speech recognition; noisy environment; nonaudible murmur microphone; sound-impaired people; stethoscope; Abstracts; Hidden Markov models; Microphones; Robustness; Speech; Speech recognition; Tin;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing Conference, 2004 12th European
Conference_Location
Vienna
Print_ISBN
978-320-0001-65-7
Type
conf
Filename
7079711
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