期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2019
卷号：19
期号：10
页码：118-124
出版社：International Journal of Computer Science and Network Security
摘要：Automatic speech recognition presents an interesting research area that has always attracted researchers to the general public. It is now giving rise to an important set of applications of a very varied nature and difficulty, involving millions of people around the world every day. In this paper, a model of speech recognition system in noisy environment is developed and analyzed. The proposed model relies on several hybrid feature extraction methods. Indeed, Teager-Energy Operator, Perceptual Wavelet Packet (TEO-PWP), Mel Cepstrum Coefficient (MFCC) and Perceptual Linear Production (PLP) are combined to construct a robust HMM based system. TIMIT database, which consist of both clean and noisy speech files recorded at different level of Speech-to-Noise Ratio (SNR, has been used for the system test. Results and observations are performed to prove the effectiveness of the proposed system relying on speech recognition rates.
