Speech Enhancement in the STFT Domain

Nonfiction, Science & Nature, Mathematics, Mathematical Analysis, Technology, Electronics
Cover of the book Speech Enhancement in the STFT Domain by Emanuël A.P. Habets, Jingdong Chen, Jacob Benesty, Springer Berlin Heidelberg
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Emanuël A.P. Habets, Jingdong Chen, Jacob Benesty ISBN: 9783642232503
Publisher: Springer Berlin Heidelberg Publication: September 18, 2011
Imprint: Springer Language: English
Author: Emanuël A.P. Habets, Jingdong Chen, Jacob Benesty
ISBN: 9783642232503
Publisher: Springer Berlin Heidelberg
Publication: September 18, 2011
Imprint: Springer
Language: English

This work addresses this problem in the short-time Fourier transform (STFT) domain. We divide the general problem into five basic categories depending on the number of microphones being used and whether the interframe or interband correlation is considered. The first category deals with the single-channel problem where STFT coefficients at different frames and frequency bands are assumed to be independent. In this case, the noise reduction filter in each frequency band is basically a real gain. Since a gain does not improve the signal-to-noise ratio (SNR) for any given subband and frame, the noise reduction is basically achieved by liftering the subbands and frames that are less noisy while weighing down on those that are more noisy. The second category also concerns the single-channel problem. The difference is that now the interframe correlation is taken into account and a filter is applied in each subband instead of just a gain.
The advantage of using the interframe correlation is that we can improve not only the long-time fullband SNR, but the frame-wise subband SNR as well. The third and fourth classes discuss the problem of multichannel noise reduction in the STFT domain with and without interframe correlation, respectively. In the last category, we consider the interband correlation in the design of the noise reduction filters. We illustrate the basic principle for the single-channel case as an example, while this concept can be generalized to other scenarios. In all categories, we propose different optimization cost functions from which we derive the optimal filters and we also define the performance measures that help analyzing them.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This work addresses this problem in the short-time Fourier transform (STFT) domain. We divide the general problem into five basic categories depending on the number of microphones being used and whether the interframe or interband correlation is considered. The first category deals with the single-channel problem where STFT coefficients at different frames and frequency bands are assumed to be independent. In this case, the noise reduction filter in each frequency band is basically a real gain. Since a gain does not improve the signal-to-noise ratio (SNR) for any given subband and frame, the noise reduction is basically achieved by liftering the subbands and frames that are less noisy while weighing down on those that are more noisy. The second category also concerns the single-channel problem. The difference is that now the interframe correlation is taken into account and a filter is applied in each subband instead of just a gain.
The advantage of using the interframe correlation is that we can improve not only the long-time fullband SNR, but the frame-wise subband SNR as well. The third and fourth classes discuss the problem of multichannel noise reduction in the STFT domain with and without interframe correlation, respectively. In the last category, we consider the interband correlation in the design of the noise reduction filters. We illustrate the basic principle for the single-channel case as an example, while this concept can be generalized to other scenarios. In all categories, we propose different optimization cost functions from which we derive the optimal filters and we also define the performance measures that help analyzing them.

More books from Springer Berlin Heidelberg

Cover of the book Electricity Distribution by Emanuël A.P. Habets, Jingdong Chen, Jacob Benesty
Cover of the book Multi-Component Acoustic Characterization of Porous Media by Emanuël A.P. Habets, Jingdong Chen, Jacob Benesty
Cover of the book Dense Matter in Compact Stars by Emanuël A.P. Habets, Jingdong Chen, Jacob Benesty
Cover of the book Cancer Immunology by Emanuël A.P. Habets, Jingdong Chen, Jacob Benesty
Cover of the book Kompendium Begutachtungswissen Geriatrie by Emanuël A.P. Habets, Jingdong Chen, Jacob Benesty
Cover of the book Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition by Emanuël A.P. Habets, Jingdong Chen, Jacob Benesty
Cover of the book Ethikberatung in der Medizin by Emanuël A.P. Habets, Jingdong Chen, Jacob Benesty
Cover of the book Business Process Management within Chemical and Pharmaceutical Industries by Emanuël A.P. Habets, Jingdong Chen, Jacob Benesty
Cover of the book Ratgeber Polyneuropathie und Restless Legs by Emanuël A.P. Habets, Jingdong Chen, Jacob Benesty
Cover of the book Energy and Water Cycles in the Climate System by Emanuël A.P. Habets, Jingdong Chen, Jacob Benesty
Cover of the book Institutional Competition between Common Law and Civil Law by Emanuël A.P. Habets, Jingdong Chen, Jacob Benesty
Cover of the book The Economics of Epidemiology by Emanuël A.P. Habets, Jingdong Chen, Jacob Benesty
Cover of the book Parallele Programmierung by Emanuël A.P. Habets, Jingdong Chen, Jacob Benesty
Cover of the book Funktionsdiagnostik in Endokrinologie, Diabetologie und Stoffwechsel by Emanuël A.P. Habets, Jingdong Chen, Jacob Benesty
Cover of the book Supply Chain Coordination in Case of Asymmetric Information by Emanuël A.P. Habets, Jingdong Chen, Jacob Benesty
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy