We introduce a new wavelet-based algorithm to enhance the quality of speech corrupted by multi-talker babble noise. The algorithm comprises three stages: The first stage classifies short frames of the noisy speech as speech-dominated or noise-dominated. We design this classifier specifically for multi-talker babble noise. The second stage performs preliminary de-nosing of noisy speech frames using oversampled wavelet transforms and parallel group thresholding. The final stage performs further denoising by attenuating residual high frequency components in the signal produced by the second stage. A significant improvement in intelligibility and quality was observed in evaluation tests of the algorithm with cochlear implant users.

我们引入了一种基于小波的新算法，以提高多说话者ba语噪声所破坏的语音质量。该算法包括三个阶段：第一阶段将嘈杂语音的短帧分类为语音为主或噪声为主。我们专门针对多说话者的bble声设计该分类器。第二阶段使用过采样的小波变换和并行组阈值处理对嘈杂的语音帧进行预消噪。最后一级通过衰减第二级产生的信号中的残留高频分量来执行进一步的降噪处理。在人工耳蜗用户的算法评估测试中，可清晰度和质量有了显着改善。