Subspace Approach for Enhancing Speech based on SVD
| Autor: | Guettal Lemya, Ghendir Said, Chemsa Ali, Hettiri Massaoud, Bessous Noureddine, Sbaa Salim, Ajgou Riadh |
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| Rok vydání: | 2018 |
| Předmět: |
Noise measurement
Computer science Noise reduction Speech recognition Filter (signal processing) 01 natural sciences Speech enhancement 030507 speech-language pathology & audiology 03 medical and health sciences symbols.namesake Signal-to-noise ratio Additive white Gaussian noise Computer Science::Sound 0103 physical sciences Singular value decomposition symbols 0305 other medical science 010301 acoustics PESQ |
| Zdroj: | 2018 International Conference on Communications and Electrical Engineering (ICCEE). |
| DOI: | 10.1109/ccee.2018.8634498 |
| Popis: | In this work, we have developed an improved approach for enhancing speech corrupted by additive white Gaussian noise. An efficient denoising approach based on singular value decomposition (SVD) and Savistky-golay filter is proposed to reduce the White Gaussian noise (WGN). In order to filter singular values (SV) that represent original speech signal, we have proposed an efficient threshold algorithm. The whole SV are extracted from Hankel matrices in the overlapping speech window frames. After selecting dominant SV by our efficient threshold, the inverse operation is performed to create the new Hankel matrices and regrouping frames to reconstruct the enhanced signal (original signal), the denoised signal is smoothed using the Savitzky-Golay filter. The proposed approach offers an improved performance of speech enhancement comparing with traditional methods in terms of Perceptual Evaluation of Speech Quality scores measure (PESQ) and segmental SNR (SegSNR). A good yield of the method is observed for the SNR values between −10 and 30 dB. |
| Databáze: | OpenAIRE |
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