Echo Noise Robust HMM Learning Model using Average Estimator LMS Algorithm
Chan-Shik Ahn, Sang-Yeob Oh · Journal of Digital Convergence · 2012
The speech recognition system can not quickly adapt to varied environmental noise factors that degrade the performance of recognition. In this paper, the echo noise robust HMM learning model using average estimator LMS algorithm is proposed. To be able to adapt to the changing echo noise HMM learning model consists of the recognition performance is evaluated. As a results, SNR of speech obtained by removing Changing environment noise is improved as average 3.1dB, recognition rate improved as 3.9%.