Fundamental Spectral Subtraction in Speech Enhancement

In the field of speech signal processing, fundamental spectral subtraction is a commonly used speech enhancement technique. The algorithm operates by processing the frequency spectrum of speech signals to eliminate noise effects, thereby improving speech signal quality. The implementation typically involves three main stages: noise estimation during non-speech segments, spectral subtraction using magnitude spectrum manipulation, and signal reconstruction through inverse FFT. This spectral subtraction program can be directly compiled and deployed, demonstrating significant effectiveness in noise reduction while maintaining speech intelligibility. The method has been widely applied in various speech enhancement applications, particularly useful for real-time processing scenarios where computational efficiency is crucial. Key implementation aspects include proper noise floor estimation, over-subtraction factor optimization, and spectral smoothing to avoid musical noise artifacts.