Loading...
Please wait, while we are loading the content...
Similar Documents
Noise Reduction of Speech Signal using Wavelet Transform with Modified Universal Threshold
| Content Provider | Semantic Scholar |
|---|---|
| Author | Aggarwal, Rajeev Sehore Rathore, Sanjay Singh Gupta, Vijay Kumar Khare, Anubhuti |
| Copyright Year | 2011 |
| Abstract | In this paper, Discrete-wavelet transform (DWT) based algorithm are used for speech signal denoising. Here both hard and soft thresholding are used for denoising. Analysis is done on noisy speech signal corrupted by babble noise at 0dB, 5dB, 10dB and 15dB SNR levels. Simulation & results are performed in MATLAB 7.10.0 (R2010a). Output SNR (Signal to Noise Ratio) and MSE (Mean Square Error) is calculated & compared using both types of thresholding methods. Soft thresholding method performs better than hard thresholding at all input SNR levels. Hard thresholding shows a maximum of 21.79 dB improvement whereas soft thresholding shows a maximum of 35.16 dB improvement in output SNR. General Terms Thresholding, multi-resolution analysis, wavelet. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.ijcaonline.org/volume20/number5/pxc3873269.pdf |
| Alternate Webpage(s) | http://www.ijcaonline.org/archives/volume20/number5/2431-3269?format=pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Algorithm Discrete wavelet transform MATLAB Mean squared error Multiresolution analysis Noise reduction Numerous Simulation Thresholding (image processing) |
| Content Type | Text |
| Resource Type | Article |