Voice Activity Detection Program with Multi-band Spectral Analysis

A Voice Activity Detection program is a crucial signal processing technique designed to identify the precise start and end points of speech segments within audio signals. This technology serves as a fundamental component in various applications including automated speech recognition systems and advanced audio processing pipelines. Multi-band analysis represents a signal processing methodology that decomposes signals into multiple frequency sub-bands, enabling more detailed examination of spectral characteristics through techniques like filter bank implementation or wavelet transforms. Entropy, a core concept from information theory, quantifies signal uncertainty and randomness - in practice calculated using probability distributions of signal amplitudes. Spectral entropy specifically measures the entropy of a signal's power spectrum, providing insights into frequency distribution patterns through FFT-based spectral analysis. The Teager energy operator offers a nonlinear energy measurement approach in the time domain that effectively captures amplitude and frequency variations simultaneously, particularly valuable for speech signal analysis where it can be implemented using difference equations. We encourage thorough study of these techniques and their practical implementation through proper algorithmic design and parameter optimization for real-world applications.