DocumentCode :
177745
Title :
Perceived quality of resonance based decomposed speech components under diotic and dichotic listening
Author :
Chin-Tuan Tan ; Selesnick, I.W. ; Avci, K.
Author_Institution :
Dept. of Otolaryngology, New York Univ., New York, NY, USA
fYear :
2014
fDate :
4-9 May 2014
Firstpage :
925
Lastpage :
929
Abstract :
This study investigates the feasibility of using binaural dichotic presentation of speech components decomposed using a recently proposed resonance-based decomposition method to release listeners from intra-speech masking and yield better perceived sound quality. Resonance-based decomposition is a nonlinear signal analysis method based not on frequency or scale but on resonance. We decomposed different categories of speech stimuli (vowels, consonants, and sentences) into low- and high-resonance component using various combination of low- and high-Q-factors {Q1, Q2}. 10 normal hearing listeners were asked to rate the perceived quality of each individual decomposed component presented diotically, and in pair presented dichotically. We found that the perceived quality rating of these resonance components when presented in pair was higher than the mean of perceived quality ratings of these resonance components when presented individually. Our result suggests that listeners were able to fuse binaural dichotic presentation of high- and low-resonance components and perceived better sound quality.
Keywords :
Q-factor; resonance; signal representation; speech processing; binaural dichotic presentation; dichotic listening; diotic listening; high-Q-factors; high-resonance component; intra-speech masking; low-Q-factors; low-resonance component; nonlinear signal analysis method; normal hearing listeners; perceived sound quality; resonance-based decomposition method; speech components; speech stimuli; Acoustics; Auditory system; Ear; Noise; Speech; Speech processing; System-on-chip; Resonance-based decomposition; binaural fusion; dichotic representation of speech;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location :
Florence
Type :
conf
DOI :
10.1109/ICASSP.2014.6853732
Filename :
6853732
Link To Document :
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