Extracting Speech Signal Spectral Envelope and Pitch Frequency Using Cepstrum Analysis

The methodology for speech signal processing involves using cepstral analysis to extract both the spectral envelope and pitch frequency of speech signals. Cepstral analysis transforms speech signals into cepstral coefficients, which effectively capture frequency-domain characteristics. This technique enables us to obtain the spectral envelope (representing the intensity distribution across different frequency components) and the pitch frequency (the fundamental frequency of the speech signal). In practical implementation, this typically involves applying Fast Fourier Transform (FFT) to convert the signal to frequency domain, computing the logarithm of the magnitude spectrum, and then performing inverse FFT to obtain the cepstrum. The lower quefrency components correspond to the spectral envelope, while the higher quefrency peaks indicate pitch frequency. These extracted features are crucial for various speech processing applications including voice recognition, speaker identification, and speech synthesis. Key algorithmic steps include windowing the signal, spectral analysis, logarithmic transformation, and cepstral peak picking for pitch detection.