Dual microphone-based speech enhancement by spectral classification and Wiener filtering
Seyoon Jeong, Subeen Lee, Minsoo Hahn
Abstract
Seyoon Jeong, Subeen Lee, Minsoo Hahn
Abstract
An efficient speech enhancement algorithm based on spectral classification and Wiener filtering is proposed. Under the assumption that the location of the target source is known, the spectral classification in the frequency domain is performed by the time delay and the magnitude ratio between dual microphone inputs. Then, the Wiener filter is applied to enhance noisy speech. Experimental results show that the proposed algorithm improves the speech quality and the recognition accuracy significantly.
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An efficient speech enhancement algorithm based on spectral classification and Wiener filtering is proposed. Under the assumption that the location of the target source is known, the spectral classification in the frequency domain is performed by the time delay and the magnitude ratio between dual microphone inputs. Then, the Wiener filter is applied to enhance noisy speech. Experimental results show that the proposed algorithm improves the speech quality and the recognition accuracy significantly.
Key concepts: Wiener filter, Speech enhancement, Microphone, Speech recognition, Computer science, Wiener deconvolution, Dual (grammatical number), Filter (signal processing)