A large number of single-channel noise-reduction algorithms have been proposed based largely on mathematical principles. Most of these algorithms, however, have been evaluated with English speech. Given the different perceptual cues used by native listeners of different languages including tonal languages, it is of interest to examine whether there are any language effects when the same noise-reduction algorithm is used to process noisy speech in different languages.

LI Junfeng, YANG Lin, ZHANG Jianping and YAN Yonghong of Institute of Acoustics, Chinese Academy of Sciences carried out a series of studies and took a comparative evaluation and investigation of various single-channel noise-reduction algorithms applied to noisy speech taken from three languages: Chinese, Japanese, and English.

In the study, clean speech signals (Chinese words and Japanese words) were first corrupted by three types of noise at two signal-to-noise ratios and then processed by five single-channel noise-reduction algorithms. The processed signals were finally presented to normal-hearing listeners for recognition. Intelligibility evaluation showed that the majority of noise-reduction algorithms did not improve speech intelligibility. Consistent with a previous study with the English language, the Wiener filtering algorithm produced small, but statistically significant, improvements in intelligibility for car and white noise conditions. Significant differences between the performances of noise-reduction algorithms across the three languages were observed.

This research result was published on the recently issued Journal of the Acousical Society of America(2011, 129 (5): 3291-3301)