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Moreover, spectral subtraction is introduced in the front end of feature extraction, and the spectral amplitude of the noise-free signal is subtracted from the spectral amplitude of the noise to obtain the spectral amplitude of the pure signal. By taking advantage of the insensitivity of speech to the phase, the phase angle information before spectral subtraction is directly used to reconstruct the signal after spectral subtraction to obtain the denoised speech. In addition, this study uses a nonlinear power function that simulates the hearing characteristics of the human ear to extract the features of the denoised speech signal and combines the English features to expand the recognition. Finally, this study analyzes the performance of the algorithm proposed in this study through comparative experiments. The research results show that the algorithm in this paper has a certain effect.<\/jats:p>","DOI":"10.3233\/jifs-189314","type":"journal-article","created":{"date-parts":[[2020,9,25]],"date-time":"2020-09-25T12:57:40Z","timestamp":1601038660000},"page":"2721-2731","source":"Crossref","is-referenced-by-count":9,"title":["Intelligent model for speech recognition based on SVM: A case study on English language"],"prefix":"10.1177","volume":"40","author":[{"given":"Qian","family":"Hou","sequence":"first","affiliation":[{"name":"School of Foreign Languages, Shaanxi University of Chinese Medicine, Shaanxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cuijuan","family":"Li","sequence":"additional","affiliation":[{"name":"Beijing 263 Enterprise Communication Co., Ltd, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min","family":"Kang","sequence":"additional","affiliation":[{"name":"School of Foreign Languages, Shaanxi University of 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