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Using Matlab to analyze and process time-frequency domain speech signals: detailed explanation of the principle
Time-frequency domain analysis is a method of analyzing signals in two dimensions: time and frequency. In speech signal processing, time-frequency domain analysis can be used to analyze the frequency characteristics, time-varying characteristics and harmonic structure of speech signals. It provides an effective tool for understanding and processing speech signals.
The following are the general principles of using Matlab for time-frequency domain speech signal analysis and processing:
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Preprocessing : First, load the speech signal and perform preprocessing. Preprocessing steps may include noise removal, filtering, speech framing, etc.
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Time domain analysis : In time domain analysis, the waveform diagram of the speech signal can be calculated. The time-varying characteristics of a speech signal can be observed by plotting its amplitude over time.
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Frequency domain analysis : Frequency domain analysis analyzes the frequency characteristics of the speech signal by converting it into the frequency domain. Common frequency domain analysis methods include Fourier Transform and Short-Time Fourier Transform. These transformations can obtain the energy distribution and spectral characteristics of the speech signal at different frequencies.
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Spectrogram : The spectrogram is one of the results of time-frequency domain analysis. It shows the speech