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: Research Article Inverse Filtering for Speech Dereverberation Less Sensitive to Noise and Room Transfer Function Fluctuations | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2007 Article ID 34013 12 pages doi 2007 34013 Research Article Inverse Filtering for Speech Dereverberation Less Sensitive to Noise and Room Transfer Function Fluctuations Takafumi Hikichi Marc Delcroix and Masato Miyoshi Media Information Laboratory NTT Communication Science Laboratories NTT Corporation 2-4 Hikaridai Seika-cho Soraku-gun Kyoto 619-0237 Japan Received 16 November 2006 Accepted 2 February 2007 Recommended by Liang-Gee Chen Inverse filtering of room transfer functions RTFs is considered an attractive approach for speech dereverberation given that the time invariance assumption of the used RTFs holds. However in a realistic environment this assumption is not necessarily guaranteed and the performance is degraded because the RTFs fluctuate over time and the inverse filter fails to remove the effect of the RTFs. The inverse filter may amplify a small fluctuation in the RTFs and may cause large distortions in the filter s output. Moreover when interference noise is present at the microphones the filter may also amplify the noise. This paper proposes a design strategy for the inverse filter that is less sensitive to such disturbances. We consider that reducing the filter energy is the key to making the filter less sensitive to the disturbances. Using this idea as a basis we focus on the influence of three design parameters on the filter energy and the performance namely the regularization parameter modeling delay and filter length. By adjusting these three design parameters we confirm that the performance can be improved in the presence of RTF fluctuations and interference noise. Copyright 2007 Takafumi Hikichi et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION Inverse filtering of
