MATLAB Implementation of Double Threshold Algorithm for Speech Endpoint Detection

The double threshold algorithm is a method used for speech endpoint detection. This algorithm enables speech endpoint detection by adjusting threshold values, and can be further enhanced by incorporating an adaptive threshold mechanism to improve detection accuracy and robustness. The double threshold algorithm is a simple yet effective approach that can be applied to various speech processing applications, such as speech recognition and speech segmentation. In MATLAB implementation, the algorithm typically involves calculating energy and zero-crossing rate features from audio signals. Key functions include frame-based processing using buffer() or enframe() functions, energy calculation using mean square values, and zero-crossing rate computation. The implementation requires setting two threshold levels - a higher threshold for speech onset detection and a lower threshold for speech termination. Adaptive threshold techniques can be implemented using moving averages or statistical approaches to dynamically adjust thresholds based on background noise characteristics. The algorithm workflow generally involves feature extraction, threshold comparison, state machine implementation for speech segment identification, and post-processing to merge adjacent segments.