Clear Filters
Clear Filters

How to use wavelet transform in "Denoise Speech Using Deep Learning Networks" example?

2 views (last 30 days)
I have implemented the example here, but I also want to do this example with wavelet. Or can I do it with another fft like? I would be very happy if you tell me how to integrate the wavelet.

Answers (1)

Akash
Akash on 28 Dec 2023
Edited: Akash on 28 Dec 2023
Hi Studentmatlaber,
I understand that you are interested in applying "wavelet analysis" for the purpose of denoising speech signals.
Signal denoising using wavelets is indeed a powerful method, and integrating it involves several key steps:-
1. Wavelet Selection and Decomposition: Choose an appropriate wavelet and the level of decomposition, 'N'. Then, perform the "wavelet decomposition" of the signal at the chosen level 'N'.
2. Thresholding Detail Coefficients: For each decomposition level from 1 to 'N', determine a suitable 'threshold' value. Apply "soft thresholding" to the detail coefficients at each level.
3. Wavelet Reconstruction: Finally, reconstruct the signal using the original approximation coefficients of level 'N' and the modified detail coefficients from levels 1 to 'N'.
For a more comprehensive understanding of the denoising process using "wavelet transforms", you can refer to the MATLAB documentation provided in the link below:-
Additionally, you may find the below provided MATLAB documentation link helpful, which demonstrates the classification of human ECG signals using "wavelet transform" in conjunction with a deep convolutional neural network:-
I hope it helps,
Thanks and regards,
Akash.

Categories

Find more on Denoising and Compression in Help Center and File Exchange

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!