Auditory masking threshold estimation for broadband noise sources with application to speech enhancement

This paper addresses issues encountered in the use of an Auditory Masking Threshold (AMT) for speech enhancement and proposes an algorithm to improve AMT estimation for broadband noise sources. We determined that while AMT estimation is fairly accurate, and hence an enhancement scheme based on AMT can suppress audible noise to a greater extent for low frequency colored noise sources, the algorithm fails to converge to the clean speech AMT for broadband communication channel noise. We propose a new AMT estimation scheme and incorporate the proposed algorithm into a previously developed enhancement framework [2].We evaluate our algorithm on a set of sentences obtained from the standard TIMIT database for at communications channel noise (FLN), and automobile highway noise (HWY) at 5 dB and 0 dB SNR levels, respectively. Evaluations were performed for 8 kHz and 16 kHz sampled speech and performance is measured with both objective and subjective assessment methods. The results show that the new AMT codebook based enhancement method is more e ective than traditional AMT methods. Also, that traditional AMT methods may not be as e ective for reduced bandwidth speech (4 kHz), or broadband interference, but that alternative AMT estimation methods can help improve convergence properties.