Cepstrum Analysis of Speech Signals
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In this context, we can perform cepstral analysis on speech signals to generate detailed information about signal waveforms and cepstrum graphs. Through cepstral analysis, which typically involves applying Fourier transforms, logarithmic operations, and inverse Fourier transforms, we can extract spectral characteristics of speech signals including pitch, amplitude, and harmonic components. These signal waveforms and cepstrum graphs, often created using MATLAB's signal processing toolbox functions like fft, log, and ifft, help us better understand and analyze speech signal properties. The implementation typically involves framing the speech signal, applying windowing functions, and computing the cepstrum using the cceps function or custom algorithms. This analysis finds practical applications in speech recognition systems, speech synthesis technologies, and various audio processing domains where feature extraction is crucial.
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