Evaluation of objective measures for intelligibility prediction of HMM-based synthetic speech in noise
Evaluation of objective measures for intelligibility prediction of HMM-based synthetic speech in noise
复制标题
噪声中基于 HMM 的合成语音清晰度预测的客观测量评估
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
Simon King
中科院分区：
文献类型：
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作者：
Cassia Valentini;J. Yamagishi;Simon King
In this paper we evaluate four objective measures of speech with regards to intelligibility prediction of synthesized speech in diverse noisy situations. We evaluated three intelligibility measures, the Dau measure, the glimpse proportion and the Speech Intelligibility Index (SII) and a quality measure, the Perceptual Evaluation of Speech Quality (PESQ). For the generation of synthesized speech we used a state of the art HMM-based speech synthesis system. The noisy conditions comprised four additive noises. The measures were compared with subjective intelligibility scores obtained in listening tests. The results show the Dau and the glimpse measures to be the best predictors of intelligibility, with correlations of around 0.83 to subjective scores. All measures gave less accurate predictions of intelligibility for synthetic speech than have previously been found for natural speech; in particular the SII measure. In additional experiments, we processed the synthesized speech by an ideal binary mask before adding noise. The Glimpse measure gave the most accurate intelligibility predictions in this situation.
