This paper presents a perceptual model based speech enhancement algorithm. The proposed algorithm measures the amount of the audible noise in the input noisy speech explicitly by using a psychoacoustic model, and decides an appropriate amount of noise reduction accordingly to achieve good noise level reduction without introducing significant distortion to the clean speech embedded in the input noisy signal. The proposed algorithm also mitigates the musical noise problem commonly encountered in conventional speech enhancement algorithms by having the amount of noise reduction adapt to the instantly estimated noise amplitude. Good performance of the proposed algorithm has been confirmed through objective and subjective tests.
Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!
This paper costs $33 for non-members and is free for AES members and E-Library subscribers.