Open Access
ARTICLE
Noise Cancellation Based on Voice Activity Detection Using Spectral Variation for Speech Recognition in Smart Home Devices
Jeong-Sik Park1, Seok-Hoon Kim2,*
1 Department of English Linguistics & Language Technology, Hankuk University of Foreign Studies, Seoul, Republic of Korea
2 Department of Electronic Commerce, Paichai University Studies, Daejeon, Republic of Korea
* Corresponding Author: Seok-Hoon Kim,
Intelligent Automation & Soft Computing 2020, 26(1), 149-159. https://doi.org/10.31209/2019.100000136
Abstract
Variety types of smart home devices have a main function of a human-machine
interaction by speech recognition. Speech recognition system may be
vulnerable to rapidly changing noises in home environments. This study
proposes an efficient noise cancellation approach to eliminate the noises
directly on the devices in real time. Firstly, we propose an advanced voice
activity detection (VAD) technique to efficiently detect speech and non-speech
regions on the basis of spectral property of speech signals. The VAD is then
employed to enhance the conventional spectral subtraction method by steadily
estimating noise signals in non-speech regions. On several experiments, our
approach achieved superior performance compared to the conventional noise
reduction approaches.
Keywords
Cite This Article
J. Park and S. Kim, "Noise cancellation based on voice activity detection using spectral variation for speech recognition in smart home devices,"
Intelligent Automation & Soft Computing, vol. 26, no.1, pp. 149–159, 2020. https://doi.org/10.31209/2019.100000136