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2010
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Speech enhancement with sparse coding in learned dictionaries

8 years 5 months ago
Speech enhancement with sparse coding in learned dictionaries
The enhancement of speech degraded by non-stationary interferers is a highly relevant and difficult task of many signal processing applications. We present a monaural speech enhancement method based on sparse coding of noisy speech signals in a composite dictionary, consisting of the concatenation of a speech and interferer dictionary, both being possibly over-complete. The speech dictionary is learned off-line on a training corpus, while an environment specific interferer dictionary is learned on-line during speech pauses. Our approach optimizes the trade-off between source distortion and source confusion, and thus achieves significant improvements on objective quality measures like cepstral distance, in the speaker dependent and independent case, in several real-world environments and at low signal-to-noise ratios. Our enhancement method outperforms state-of-the-art methods like multi-band spectral subtraction and approaches based on vector quantization.
Christian D. Sigg, Tomas Dikk, Joachim M. Buhmann
Added 11 Feb 2011
Updated 11 Feb 2011
Type Journal
Year 2010
Where ICASSP
Authors Christian D. Sigg, Tomas Dikk, Joachim M. Buhmann
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