Abstract
While most single-channel noise reduction algorithms fail to improve speech intelligibility, the ideal binary mask (IBM) has demonstrated
substantial intelligibility improvements for both normal- and impaired-hearing listeners. However, this approach exploits oracle knowledge of
the target and interferer signals to preserve only the time-frequency regions that are target-dominated. Single-channel noise suppression
algorithms trying to approximate the IBM using locally estimated signal-to-noise ratios without oracle knowledge have had limited success.
Thought of in another way, the IBM exploits the disjoint placement of the target and interferer in time and frequency to create a time-frequency
signal representation that is more sparse (i.e., has fewer non-zeros). In recent work (submitted to ICASSP 2013) we have introduced a novel
time-frequency masking algorithm based on a sparse approximation algorithm from the signal processing literature. However, the algorithm
employs a non-causal estimator. The present work introduces an improved de-noising algorithm that uses more realistic frame-based (causal)
computations to estimate a binary mask.
Original language | English |
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Title of host publication | Proceedings of Meetings on Acoustics |
Number of pages | 9 |
Publication date | 2013 |
Article number | 055037 |
DOIs | |
Publication status | Published - 2013 |
Event | 21st International Congress on Acoustics - Montreal, Canada Duration: 2 Jun 2013 → 7 Jun 2013 Conference number: 21 http://www.ica2013montreal.org/ |
Conference
Conference | 21st International Congress on Acoustics |
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Number | 21 |
Country/Territory | Canada |
City | Montreal |
Period | 02/06/2013 → 07/06/2013 |
Internet address |