TY - GEN
T1 - Speech recognition in a home environment using parallel decoding with GMM-based noise modeling
AU - Machida, Kohei
AU - Nose, Takashi
AU - Ito, Akinori
PY - 2014/2/12
Y1 - 2014/2/12
N2 - In this paper, we propose a method for noise-robust speech recognition in a home environment based on noise modeling and parallel decoding. There are three basic ideas of the proposed method. First, we model the noise signals observed in the environment using a GMM. Second, we generate multiple noise-reduced signals using the mean vectors of the GMM and decode the signals in parallel. Third, we choose the best recognition result from the multiple recognition results based on the confidence score. The proposed method is very simple and straightforward, yet effective compared with simple noise reduction. The experiments proved that the proposed method is effective for not only noise signals in the database but also for those in the real home environment.
AB - In this paper, we propose a method for noise-robust speech recognition in a home environment based on noise modeling and parallel decoding. There are three basic ideas of the proposed method. First, we model the noise signals observed in the environment using a GMM. Second, we generate multiple noise-reduced signals using the mean vectors of the GMM and decode the signals in parallel. Third, we choose the best recognition result from the multiple recognition results based on the confidence score. The proposed method is very simple and straightforward, yet effective compared with simple noise reduction. The experiments proved that the proposed method is effective for not only noise signals in the database but also for those in the real home environment.
KW - Confidence measure
KW - FBANK
KW - Gaussian Mixture Model
KW - Noise modeling
KW - Speech recognition in noise
UR - http://www.scopus.com/inward/record.url?scp=84983185839&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84983185839&partnerID=8YFLogxK
U2 - 10.1109/APSIPA.2014.7041622
DO - 10.1109/APSIPA.2014.7041622
M3 - Conference contribution
AN - SCOPUS:84983185839
T3 - 2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014
BT - 2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014
Y2 - 9 December 2014 through 12 December 2014
ER -