SPEECH ENHANCEMENT BASED CONCEPTUALLY ON AUDITORY EVIDENCE

This paper addresses the problem of enhancing speech degraded by stationary and nonstationary additive white noise. We have explored a new idea, enhancing speech based on auditory evidence, for this traditional topic. Distinguishing different objectives for heavy and light noise interference, two related algorithms have been developed. For speech degraded by heavy noise, the improvement in signal-to-noise ratio (SNR) is as high as 12 dB; for lightly noisy speech, the improvement is modest and decreases as the SNR of the noisy speech increases. We use quantizing noise to assess the capacity of reducing nonstationary noise using our algorithms; a significant reduction of such noise and an improvement in speech quality have been achieved. The advantages of the proposed algorithms for speech enhancement include no need for prior knowledge of the noise and only a modest computational requirement.