TAILIEUCHUNG - báo cáo hóa học:" Dereverberation and denoising based on generalized spectral subtraction by multi-channel LMS algorithm using a small-scale microphone array"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Dereverberation and denoising based on generalized spectral subtraction by multi-channel LMS algorithm using a small-scale microphone array | Wang et al. EURASIP Journal on Advances in Signal Processing 2012 2012 12 http content 2012 1 12 o EURASIP Journal on Advances in Signal Processing a SpringerOpen Journal RESEARCH Open Access Dereverberation and denoising based on generalized spectral subtraction by multi-channel LMS algorithm using a small-scale microphone array Longbiao Wang Kyohei Odani and Atsuhiko Kai Abstract A blind dereverberation method based on power spectral subtraction SS using a multi-channel least mean squares algorithm was previously proposed to suppress the reverberant speech without additive noise. The results of isolated word speech recognition experiments showed that this method achieved significant improvements over conventional cepstral mean normalization CMN in a reverberant environment. In this paper we propose a blind dereverberation method based on generalized spectral subtraction GSS which has been shown to be effective for noise reduction instead of power SS. Furthermore we extend the missing feature theory MFT which was initially proposed to enhance the robustness of additive noise to dereverberation. A one-stage dereverberation and denoising method based on GSS is presented to simultaneously suppress both the additive noise and nonstationary multiplicative noise reverberation . The proposed dereverberation method based on GSS with MFT is evaluated on a large vocabulary continuous speech recognition task. When the additive noise was absent the dereverberation method based on GSS with MFT using only 2 microphones achieves a relative word error reduction rate of and compared to the dereverberation method based on power SS and the conventional CMN respectively. For the reverberant and noisy speech the dereverberation and denoising method based on GSS achieves a relative word error reduction rate of compared to the conventional CMN with GSS-based additive noise reduction method. We also analyze the effective factors of the compensation

TÀI LIỆU LIÊN QUAN
Đã phát hiện trình chặn quảng cáo AdBlock
Trang web này phụ thuộc vào doanh thu từ số lần hiển thị quảng cáo để tồn tại. Vui lòng tắt trình chặn quảng cáo của bạn hoặc tạm dừng tính năng chặn quảng cáo cho trang web này.