Energy-constrained signal subspace method for speech enhancement and recognition
Jun Huang, Yunxin Zhao · IEEE Signal Processing Letters · 1997
In this letter, an improved signal-subspace-based speech enhancement algorithm is proposed for automatic speech recognition under an additive noise environment. The key idea is to match the short-time energy of the enhanced speech signal to the unbiased estimate of the short-time energy of the clean speech, which is proven very effective for improving the estimation of the low-energy segments of continuous speech under low signal-to-noise ratio (SNR) conditions. Experimental results show significant improvement in both the segmental SNR and the word recognition accuracy of the enhanced speech under SNR conditions of 10-20 dB.