mohammadnabia / Matlab_DSP_Energy_ZCR_Autocorrelation

In this repository, we first read the file of a signal in Matlab and then calculate for that signal the energy value of the short time, the magnitude of the short time, and the Zero crossing rate on the short time. After seeing the output of the above values, we check the autocorrelation for vowels and non-vowels in our selected part of the file.

Matlab_DSP_Energy_ZCR_Autocorrelation

Overview

Welcome to the Voice Signal Analysis Toolbox repository! This toolbox is designed to analyze voice signals in WAV format. It includes functionalities to calculate energy, magnitude, and zero-crossing rate and perform Autocorrelation for voiced and unvoiced segments. Explanatory comments and examples accompany the code. In this repository, we first read the file of a signal in Matlab and then calculate for that Signal the energy value of the short time, the magnitude of the short time, and the zero crossing rate of the short time. After seeing the output of the above values, we check the Autocorrelation for voiced and unvoiced in our selected part of the file.

Code Overview

Reading the WAV Signal

The toolbox starts by reading the WAV signal using the readwav function. It extracts essential parameters such as the Signal (Y), sampling frequency (FS), waveform mode (WMODE), and frame index (FIDX).

[Y, FS, WMODE, FIDX] = readwav('Mlvsp8.wav');

Listening to the Signal

You can listen to a selected portion of the voice signal to get an auditory sense of the analyzed segment.

player = audioplayer(Y(1:1:31946), FS);
play(player);

Energy, Magnitude, and Zero-Crossing Rate Calculation

Calculate and display the Signal's energy, magnitude, and zero-crossing rate.

Energy = sum(Y(1:1:31946).^2);
Magnitude = sum(abs(Y(1:1:31946)));
ZCR = calculateZeroCrossingRate(Y);

Autocorrelation Analysis

Perform Autocorrelation for both voiced and unvoiced segments, plotting the results.

[AutoCorrelationVoiced, lagsVoiced] = autocorrAnalysis(Y(15170:1:16468));
[AutoCorrelationUnvoiced, lagsUnvoiced] = autocorrAnalysis(Y(17152:1:18402));

Results

ZCR, Energy, Magnitude:

the output for ZCR, Energy & Magnitude

Autocorrelation:

the output for Autocorrelation of a voiced and unvoiced

Contributing

I want you to know that contributions to this repository are welcome. If you have any improvements, bug fixes, or additional examples related to voice signal analysis, please feel free to submit a pull request. Let's collaborate and make this repository a valuable resource for the community.

License

This project is licensed under the MIT License. You can use, modify, and distribute the code as the license permits.

Happy coding! 👾

---

Additional information: The waveform I used in this project is a Farsi voice that says, "Turn on the recorder" to the computer. The file of this waveform is named Mlvsp8.wav. You can access this file in the repository.