TY - GEN
T1 - A Time-Weighted Method for Predicting the Intelligibility of Speech in the Presence of Interfering Sounds
AU - Song, Mingjie
AU - Chen, Fei
AU - Wu, Xihong
AU - Chen, Jing
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/9/10
Y1 - 2018/9/10
N2 - The speech intelligibility index (SII) has been widely used as an objective method of predicting speech intelligibility, but its traditional form is most effective predicting speech intelligibility scores under stationary noise but not more challenging conditions (e.g., competing noise interference). To address this limitation, the present work extended the SII model to predict the intelligibility of speech in both steady speech-spectral noise (SSN) and dual-talker speech (DTS), by using a time-weighted function that accounted for the relative perceptual importance of vowels and consonants in speech intelligibility. The performance of the new time-weighted SII (TW-SII) was compared to the other two well-known methods, i.e., the time-averaged SII (TA-SII) and coherence SII (CSII). Experimental results showed the intelligibility prediction accuracy of the three methods was similar for speech in SSN, but the prediction by TW-SII was more accurate than those by TA-SII and CSII for speech in DTS. The possible applications and limitations of the present intelligibility model were analyzed and discussed.
AB - The speech intelligibility index (SII) has been widely used as an objective method of predicting speech intelligibility, but its traditional form is most effective predicting speech intelligibility scores under stationary noise but not more challenging conditions (e.g., competing noise interference). To address this limitation, the present work extended the SII model to predict the intelligibility of speech in both steady speech-spectral noise (SSN) and dual-talker speech (DTS), by using a time-weighted function that accounted for the relative perceptual importance of vowels and consonants in speech intelligibility. The performance of the new time-weighted SII (TW-SII) was compared to the other two well-known methods, i.e., the time-averaged SII (TA-SII) and coherence SII (CSII). Experimental results showed the intelligibility prediction accuracy of the three methods was similar for speech in SSN, but the prediction by TW-SII was more accurate than those by TA-SII and CSII for speech in DTS. The possible applications and limitations of the present intelligibility model were analyzed and discussed.
KW - Consonant
KW - Speech intelligibility index
KW - Time-weighted
KW - Vowel
UR - http://www.scopus.com/inward/record.url?scp=85054254500&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2018.8462124
DO - 10.1109/ICASSP.2018.8462124
M3 - Conference contribution
AN - SCOPUS:85054254500
SN - 9781538646588
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 5589
EP - 5593
BT - 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
Y2 - 15 April 2018 through 20 April 2018
ER -