A hybrid speech enhancement system based on HMM and spectral subtraction

In this paper we describe a speech enhancement system based on spectral subtraction and a proposed AR-HMM-based pause detection algorithm. When trained off-line with limited types of environmental noises, the system performs well under almost all types of environmental noises. We show that the proposed pause detection method is at least one order of magnitude faster than the traditional correlation-based algorithms, and at the same time, has a better performance in locating long pauses in noisy speech. A method of musical noise reduction is also applied in this work. The hybrid speech enhancement system is implemented on a Pentium-166 PC. Using a standard sound card or digital audio interface, the system works in real-time with a negligible solid delay. The speech enhancement experiments using the hybrid system and the conventional spectral subtraction method clearly demonstrate the superiority of the proposed pause detection approach.