스펙트럼사상학습을 이용한 잡음환경에서의 한국어숫자음인식 = Korean Digit Recognition Under Noise Environment Using Spectral Mapping Training

다국어 초록 (Multilingual Abstract)

This paper presents the Korean digit recognition method under noise environment using the spectral mapping training based on static supervised adaptation algorithm. In the presented recognition method, as a result of spectral mapping from one space of noisy speech spectrum to another space of speech spectrum without noise, spectral distortion of noisy speech is improved, and the recognition rate is higher than that of the conventional method using VQ (vector quatization) and DTW(dynamic time warping) without noise processing, and even when SNR level is 0dB, the recognition rate is 10 times of that using the conventional method. It has been confirmed that the spectral mapping training has an ability to improve the recognition performance for speech in noise environment.