The Research On The Speech Recognition System In The Noisy Environment

With the rapid progress of modern computer technology and speech technology, communicating through speech with computer becomes a hallmark of the development of computer technology. Accordingly, speech recognition and synthesis become a research field that need to develop urgently. Speech recognition systems can obtain a very high accuracy for clean speech , but their performance will degrade rapidly in noisy environments owing to the mismatch between the acoustic models and the testing speech. Therefore, noise robust technology is a very crucial problem for the real application of speech recognition.We focus on the discussion of the application of three key speech features- Linear Prediction Coefficients(LPC), Linear Prediction Cepstrum Coefficient(LPCC), Mel Frequency Cepstrum Coefficients(MFCC) and of general methods of speech recognition, including the Dynamic Time Warping(DTW ) and Hidden Markov Model(HMM).We simulate the speech recognition using the speech feature MFCC and HMM. Then We discus three methods of noise robust technologies in speech enhancement, speech model compensation for noisy environments and extraction of robust speech features. The algorithm of endpoint detection in speech recognition is improved. Lastly,An algorithm for endpoint detection which based on cross correlation function is proposed. The experimental results show the performance of endpoint detection can be improved by this method in various SNR environments. But the real-time is a little worse .