Multi-band maximum a posteriori multi-transformation algorithm based on the discriminative combination
Wei Sun, Zhenyang Wu, Hong-Mei Hu, Yumin Zeng · 2005
According to auditory characteristics of human's hearing system, a multi-band maximum a posteriori multi-transformation algorithm based on the discriminative combination is developed to improve the performance of speech recognition systems in noisy environment. The algorithm utilizes the difference between noise's spectrum and speech's spectrum, and the different effects of noise on recognition performance in different frequency bands. It compensates the effect of noise with a discriminative function and maximum a posteriori multi-transformation. Experimental results show that the proposed algorithm outperforms the maximum a posterior linear regression algorithm. The results also show that the utilization of effective band with information redundancy helps to improve the recognition performance.