Rapid adaptation algorithm based regression analysis for speech recognition

Least Square Linear Regression (LSLR) algorithm was given by regression analysis method. LSLR was the equivalent algorithm of traditional Maximum Likelihood Linear Regression (MLLR). The corresponding multilinear regression model was found. The multicollinearity of LSLR caused the performance degradation when adaptation data was limited. Pseudo Adaptation Data (PAD) method was proposed for decreasing the degree of multicollinearity. Experimental results showed that PAD outperforms MLLR when adaptation data was sparse and converges to the MLLR/LSLR performance when more adaptation data was available.