Explore MATLAB source code curated for "语音端点检测" with clean implementations, documentation, and examples.
Exploration of double threshold-based speech endpoint detection, including signal quantization techniques, LPCC algorithm implementation, and comprehensive calculation of cepstral parameters.
Voice activity detection using spectral subtraction method, incorporating techniques such as speech enhancement, noise reduction, spectral subtraction, windowing, and endpoint detection algorithms with code implementation details
A comprehensive MATLAB program for voice activity detection, featuring complete source files, thoroughly debugged and fully functional
Self-developed voice activity detection program utilizing subband spectral entropy analysis during postgraduate studies - fully functional with verified accuracy and excellent performance.
This robust voice activity detection method utilizing adaptive subband spectral entropy can be implemented for speech enhancement and endpoint detection applications with improved performance in noisy environments.
A voice activity detection program that utilizes cepstral analysis methodology for effective speech signal endpoint detection with reliable performance
Voice activity detection is a crucial preprocessing step for extracting feature parameters in speech compression applications, and this program provides a practical MATLAB implementation of this process with signal processing algorithm explanations for speech technology learners.
A MATLAB-based voice activity detection program designed to identify speech start and end points in audio signals, featuring robust algorithm implementation with code-level insights.
Robust voice activity detection algorithm based on adaptive sub-band spectral entropy with enhanced code implementation details
Voice Activity Detection (VAD) serves as a fundamental technology in speech recognition with extensive applications across both commercial and civil domains. Accurate endpoint detection becomes particularly challenging in low signal-to-noise ratio (SNR) environments, especially during silent segments or transitional periods before and after phonation.