Investigation of objective measures for intelligibility prediction of noise-reduced speech for Chinese, Japanese, and...

Many objective measures have been reported to predict speech intelligibility in noise, most of which were designed and evaluated with English speech corpora. Given the different perceptual cues used by native listeners of different languages, examining whether there is any language effect when the same objective measure is used to predict speech intelligibility in different languages is of great interest, particularly when non-linear noise-reduction processing is involved. In the present study, an extensive evaluation is taken of objective measures for speech intelligibility prediction of noisy speech processed by noise-reduction algorithms in Chinese, Japanese, and English. Of all the objective measures tested, the short-time objective intelligibility (STOI) measure produced the most accurate results in speech intelligibility prediction for Chinese, while the normalized covariance metric (NCM) and middle-level coherence speech intelligibility index ( CSIIm) incorporating the signal-dependent band-importance functions (BIFs) produced the most accurate results for Japanese and English, respectively. The objective measures that performed best in predicting the effect of non-linear noise-reduction processing in speech intelligibility were found to be the BIF-modified NCM measure for Chinese, the STOI measure for Japanese, and the BIF-modified CSIIm measure for English. Most of the objective measures examined performed differently even under the same conditions for different languages.