Multistage switched adaptive filtering approach for denoising speech signals of Parkinson's Disease-affected patients
Recording the speech signals of Parkinson's Disease (PD)-affected patients is challenging due to the surrounding noise. Therefore there is a need to denoise the signals. This paper proposes an Adaptive Noise Canceller-based model for signal denoising. This paper introduces an optimal adaptive f...
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Springer Birkhauser
2023
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my.um.eprints.393762023-11-28T07:52:01Z http://eprints.um.edu.my/39376/ Multistage switched adaptive filtering approach for denoising speech signals of Parkinson's Disease-affected patients Pauline, S. Hannah Dhanalakshmi, Samiappan Kumar, R. Narayanamoorthi, R. Lai, Khin Wee TK Electrical engineering. Electronics Nuclear engineering Recording the speech signals of Parkinson's Disease (PD)-affected patients is challenging due to the surrounding noise. Therefore there is a need to denoise the signals. This paper proposes an Adaptive Noise Canceller-based model for signal denoising. This paper introduces an optimal adaptive filter structure using a signed LMS algorithm to compute the best estimate of a clean signal. A noise-corrupted signal is sent across multiple adaptive filters connected in series. Multiple stages are added automatically, and the filtering algorithm for each stage is also adjusted automatically. The proposed multi-stage switched adaptive filter model is tested for reducing the noise from a speech signal recorded from Parkinson's Disease-affected patients and corrupted by Gaussian signals of different input SNR levels. The simulation results prove that the proposed filter model performs remarkably well and provides 20-30 dB higher SNR values than the existing cascaded LMS filter models. The MSE value is improved by 85-97%, and the PSNR values are increased by 7 dB. Using the Sign LMS algorithm in the proposed filter model offers a cost-effective hardware implementation of Adaptive Noise Canceller with high accuracy. Springer Birkhauser 2023-04 Article PeerReviewed Pauline, S. Hannah and Dhanalakshmi, Samiappan and Kumar, R. and Narayanamoorthi, R. and Lai, Khin Wee (2023) Multistage switched adaptive filtering approach for denoising speech signals of Parkinson's Disease-affected patients. Circuits Systems and Signal Processing, 42 (4). pp. 2259-2282. ISSN 0278-081X, DOI https://doi.org/10.1007/s00034-022-02211-3 <https://doi.org/10.1007/s00034-022-02211-3>. 10.1007/s00034-022-02211-3 |
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TK Electrical engineering. Electronics Nuclear engineering Pauline, S. Hannah Dhanalakshmi, Samiappan Kumar, R. Narayanamoorthi, R. Lai, Khin Wee Multistage switched adaptive filtering approach for denoising speech signals of Parkinson's Disease-affected patients |
| description |
Recording the speech signals of Parkinson's Disease (PD)-affected patients is challenging due to the surrounding noise. Therefore there is a need to denoise the signals. This paper proposes an Adaptive Noise Canceller-based model for signal denoising. This paper introduces an optimal adaptive filter structure using a signed LMS algorithm to compute the best estimate of a clean signal. A noise-corrupted signal is sent across multiple adaptive filters connected in series. Multiple stages are added automatically, and the filtering algorithm for each stage is also adjusted automatically. The proposed multi-stage switched adaptive filter model is tested for reducing the noise from a speech signal recorded from Parkinson's Disease-affected patients and corrupted by Gaussian signals of different input SNR levels. The simulation results prove that the proposed filter model performs remarkably well and provides 20-30 dB higher SNR values than the existing cascaded LMS filter models. The MSE value is improved by 85-97%, and the PSNR values are increased by 7 dB. Using the Sign LMS algorithm in the proposed filter model offers a cost-effective hardware implementation of Adaptive Noise Canceller with high accuracy. |
| format |
Article |
| author |
Pauline, S. Hannah Dhanalakshmi, Samiappan Kumar, R. Narayanamoorthi, R. Lai, Khin Wee |
| author_facet |
Pauline, S. Hannah Dhanalakshmi, Samiappan Kumar, R. Narayanamoorthi, R. Lai, Khin Wee |
| author_sort |
Pauline, S. Hannah |
| title |
Multistage switched adaptive filtering approach for denoising speech signals of Parkinson's Disease-affected patients |
| title_short |
Multistage switched adaptive filtering approach for denoising speech signals of Parkinson's Disease-affected patients |
| title_full |
Multistage switched adaptive filtering approach for denoising speech signals of Parkinson's Disease-affected patients |
| title_fullStr |
Multistage switched adaptive filtering approach for denoising speech signals of Parkinson's Disease-affected patients |
| title_full_unstemmed |
Multistage switched adaptive filtering approach for denoising speech signals of Parkinson's Disease-affected patients |
| title_sort |
multistage switched adaptive filtering approach for denoising speech signals of parkinson's disease-affected patients |
| publisher |
Springer Birkhauser |
| publishDate |
2023 |
| url |
http://eprints.um.edu.my/39376/ |
| _version_ |
1783876687794012160 |
| score |
13.251813 |