English teaching man-machine interaction system and method thereof
A method of human-computer interaction and English teaching technology, applied in speech analysis, semantic analysis, speech recognition, etc., can solve the problems of low intelligence of English teaching equipment, low real-time and interactive oral training, lack of oral English learning environment, etc. problems, to achieve the effect of improving practicability and data identification efficiency, meeting real-time and interactive requirements, reducing demand and labor cost input
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Embodiment 1
[0068] Such as figure 1 As shown, the present embodiment provides a human-computer interaction system for English teaching, including a human-computer interaction unit, a semantic analysis unit, and a cloud data center, and the human-computer interaction unit is respectively connected to the semantic analysis unit and the cloud data center by communication;
[0069] The human-computer interaction unit is used to collect the user's user login information and spoken English video data, send the user login information to the cloud data center for user verification, and send the collected spoken English audio data to the semantic analysis unit and the cloud data center for semantic analysis. Analyze and broadcast the corresponding English response video data;
[0070] The semantic analysis unit is used to extract the spoken English audio data included in the spoken English video data, identify the spoken English audio data to obtain corresponding spoken English text data, and anal...
Embodiment 2
[0077] This embodiment is an improvement based on the technical solution of embodiment 1, and its difference from embodiment 1 is:
[0078] A human-computer interaction method for English teaching, such as figure 2 As shown, the human-computer interaction system based on English teaching includes the following steps:
[0079] Perform user authentication, including the following steps:
[0080] The human-computer interaction unit collects user login information and sends it to the cloud data center. If the user login information is abnormal data, the user face image data of the current user is collected, and the image recognition module performs face identity verification based on the current user face image data. Otherwise, the cloud data center judges whether the current user is a known user according to the user login information;
[0081] If the current user's face image data cannot be matched to the user database of known users, the verification failure information is r...
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