Priori knowledge-based pronunciation evaluation and diagnosis system

Abstract

The invention discloses a priori knowledge-based pronunciation evaluation and diagnosis system, which comprises a voice preprocessing unit, a pronunciation evaluation unit, an evaluation confirmation and diagnosis unit, a model and priori knowledge base unit, and an evaluation information and diagnosis information output unit. The priori knowledge is applied in two aspects of the priori knowledge-based pronunciation evaluation and diagnosis system: firstly, performing correction on the traditional posterior probability by using the priori knowledge of the mispronunciation of a confusable phoneme pair, and adopting the corrected posterior probability to perform the pronunciation evaluation; secondly, using the priori knowledge of the discriminative feature of the confusable phoneme pair, adopting a discriminative feature and sorter-based method, confirming an evaluation result, and obtaining better evaluation performance to provide the diagnostic information for a learner from the morebasic and fine standpoint and help the learner to correct and improve the pronunciation. The priori knowledge-based pronunciation evaluation and diagnosis system can meet the requirement on high reliability and high accuracy in learning and testing Putonghua, and is an innovative and effective method.

Description

technical field [0001] The invention relates to the technical field of computer-aided language learning and speech processing, in particular to a pronunciation evaluation and diagnosis system based on prior knowledge. Background technique [0002] Our country's traditional Mandarin learning and testing methods are currently facing a prominent contradiction between the urgent need for the promotion of Mandarin and the lack of learning and testing conditions. Putonghua learning needs to correct students' individual problems and requires long-term interactive communication. These conditions cannot be met by the current teachers. At the same time, the oral test is an effective means of testing learning outcomes, but time-consuming and labor-intensive manpower organization, inevitable fairness issues, and difficulty in providing feedback have become bottlenecks restricting the development of the Mandarin oral test. To solve the above problems, computer-aided language learning an...

AI Technical Summary

Problems solved by technology

[0004] The problems faced by the above method are: firstly, the accuracy of pronunciation evaluation and diagnosis is not very high, especially for some confusing phoneme pairs that often make mistakes in actual pronunciation and have very close pronunciations.

Secondly, it can only give corresponding scores according to the level of pronunciation of learners, and cannot give more instructive diagnostic information

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