Multi-band maximum a posteriori multi-transformation algorithm based on the discriminative combination

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.