Pitch Frequency Extraction from Speech Signals

This article presents a MATLAB-based approach for extracting pitch frequency from speech signals. The implemented algorithm utilizes both autocorrelation and cepstral analysis methods to accurately detect fundamental frequency (F0) patterns. Key functions include frame-based processing with Hanning windows, peak detection algorithms for frequency estimation, and voice activity detection to distinguish between voiced and unvoiced segments.The program supports customizable parameters such as frame size (typically 20-30 ms), overlap percentage, and frequency range constraints for robust pitch tracking across different speaking styles. By implementing spectral analysis through FFT and employing median filtering for smoothing pitch contours, the solution provides reliable frequency extraction suitable for speech processing applications. This reusable MATLAB implementation enables efficient batch processing of multiple speech files with visualization tools for pitch contour analysis and validation.