TY - GEN
T1 - A new efficient measure for accuracy prediction and its application to multistream-based unsupervised adaptation
AU - Ogawa, Tetsuji
AU - Mallidi, Sri Harish
AU - Dupoux, Emmanuel
AU - Cohen, Jordan
AU - Feldman, Naomi H.
AU - Hermansky, Hynek
PY - 2016/1/1
Y1 - 2016/1/1
N2 - A new efficient measure for predicting estimation accuracy is proposed and successfully applied to multistream-based unsupervised adaptation of ASR systems to address data uncertainty when the ground-truth is unknown. The proposed measure is an extension of the M-measure, which predicts confidence in the output of a probability estimator by measuring the divergences of probability estimates spaced at specific time intervals. In this study, the M-measure was extended by considering the latent phoneme information, resulting in an improved reliability. Experimental comparisons carried out in a multistream-based ASR paradigm demonstrated that the extended M-measure yields a significant improvement over the original M-measure, especially under narrow-band noise conditions.
AB - A new efficient measure for predicting estimation accuracy is proposed and successfully applied to multistream-based unsupervised adaptation of ASR systems to address data uncertainty when the ground-truth is unknown. The proposed measure is an extension of the M-measure, which predicts confidence in the output of a probability estimator by measuring the divergences of probability estimates spaced at specific time intervals. In this study, the M-measure was extended by considering the latent phoneme information, resulting in an improved reliability. Experimental comparisons carried out in a multistream-based ASR paradigm demonstrated that the extended M-measure yields a significant improvement over the original M-measure, especially under narrow-band noise conditions.
UR - http://www.scopus.com/inward/record.url?scp=85019079432&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85019079432&partnerID=8YFLogxK
U2 - 10.1109/ICPR.2016.7899966
DO - 10.1109/ICPR.2016.7899966
M3 - Conference contribution
AN - SCOPUS:85019079432
T3 - Proceedings - International Conference on Pattern Recognition
SP - 2222
EP - 2227
BT - 2016 23rd International Conference on Pattern Recognition, ICPR 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd International Conference on Pattern Recognition, ICPR 2016
Y2 - 4 December 2016 through 8 December 2016
ER -