@article{ref1,
title="Objective measures for predicting speech intelligibility in noisy conditions based on new band-importance functions",
journal="Journal of the Acoustical Society of America",
year="2009",
author="Ma, Jianfen and Hu, Yi and Loizou, Philipos C.",
volume="125",
number="5",
pages="3387-3405",
abstract="The articulation index (AI), speech-transmission index (STI), and coherence-based intelligibility metrics have been evaluated primarily in steady-state noisy conditions and have not been tested extensively in fluctuating noise conditions. The aim of the present work is to evaluate the performance of new speech-based STI measures, modified coherence-based measures, and AI-based measures operating on short-term (30 ms) intervals in realistic noisy conditions. Much emphasis is placed on the design of new band-importance weighting functions which can be used in situations wherein speech is corrupted by fluctuating maskers. The proposed measures were evaluated with intelligibility scores obtained by normal-hearing listeners in 72 noisy conditions involving noise-suppressed speech (consonants and sentences) corrupted by four different maskers (car, babble, train, and street interferences). Of all the measures considered, the modified coherence-based measures and speech-based STI measures incorporating signal-specific band-importance functions yielded the highest correlations (r=0.89-0.94). The modified coherence measure, in particular, that only included vowel/consonant transitions and weak consonant information yielded the highest correlation (r=0.94) with sentence recognition scores. The results from this study clearly suggest that the traditional AI and STI indices could benefit from the use of the proposed signal- and segment-dependent band-importance functions.<p /> <p>Language: en</p>",
language="en",
issn="0001-4966",
doi="10.1121/1.3097493",
url="http://dx.doi.org/10.1121/1.3097493"
}