Based on the research and analysis of speech recognition system and neural network principle, combined with English related decision tree, this paper completes the construction and design of English speech recognition based on hybrid frame and series frame neural system network. Combined with relevant information, this paper analyzes the influencing factors of language recognition technology in English collection under neural network. This paper proposes a method of English Corpus collection. Through the speech recognition technology under the neural network, experiments are carried out by using the neural network algorithm, K-means clustering algorithm and HMM / Ann cascade system to analyze the influencing factors of speech recognition technology based on the neural network in English collection. Finally, from the English accent, the amount of speech information make a detailed analysis of the proportion of speech fuzziness, speech speed and environmental interference, so as to draw a conclusion.
<p>With the increasingly frequent economic and cultural exchanges between countries, in order to better promote the exchange between China and the world, it is necessary to improve the practicality of English teaching, so as to better meet the needs of daily communication. English using ability plays an irreplaceable role in national construction, however, as Chinese universities are still affected by exam-oriented education in English teaching, they are more inclined to use professional terms in English knowledge teaching which are rarely used in real life. As a result, it is difficult for students to understand and use English. Therefore, this paper mainly discusses the optimization strategies based on the current situation of college English teaching, so as to provide better guarantee for the improvement of college students' comprehensive English ability.</p>
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