Objective measures for predicting speech intelligibility in noisy conditions based on new band-importance functions
Objective measures for predicting speech intelligibility in noisy conditions based on new band-importance functions
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DOI：
10.1121/1.3097493
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发表时间：
2009-05-01
影响因子：
2.4
通讯作者：
Loizou, Philipos C.
中科院分区：
文献类型：
--
作者：
Ma, Jianfen;Hu, Yi;Loizou, Philipos C.
清晰度指数（AI），语音传输指数（STI），和基于相干性的可懂度指标已主要在稳态噪声条件下进行了评估，并没有在波动的噪声条件下进行广泛的测试。本工作的目的是评估新的语音为基础的STI措施，修改后的连贯性为基础的措施，和AI为基础的措施，在现实的嘈杂条件下短期（30毫秒）的间隔操作的性能。重点放在设计新的频带重要性加权函数，可用于语音被破坏的情况下，波动掩蔽。建议的措施进行了评估与可懂度分数获得正常听力的听众在72嘈杂的条件下，涉及噪声抑制语音（辅音和句子）损坏的四个不同的掩蔽（汽车，串音，火车和街道干扰）。在所有考虑的措施中，修改后的相干性为基础的措施和语音为基础的STI措施，结合信号特定的频带重要性函数产生了最高的相关性（r=0.89-0.94）。修改后的连贯性措施，特别是，只包括元音/辅音过渡和弱辅音信息产生了最高的相关性（r=0.94）与句子识别分数。这项研究的结果清楚地表明，传统的AI和STI指数可以受益于使用建议的信号和段依赖的频带重要性函数。(c)2009年，美国声学学会。[DOI：10.1121/1.3097493]
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. (c) 2009 Acoustical Society of America. [DOI: 10.1121/1.3097493]