Voice evaluating method and device based on pronunciation rhythms

Abstract

The invention relates to a voice evaluating method and a voice evaluating device based on pronunciation rhythms. The device comprises a GMM (Gaussian mixture model) obtaining unit, a likelihood obtaining unit and an evaluation model obtaining unit, wherein the GMM obtaining unit is used for selecting out training data from an evaluated voice, extracting the rhythm characteristic parameter of the training data and then training, so as to obtain the GMM; the likelihood obtaining unit is used for extracting the rhythm characteristic parameter of the evaluated voice as the input of the GMM model and obtaining corresponding likelihood value after GMM matching; and the evaluation model obtaining unit is used for evaluating the pronunciation rhythms of the evaluated voice according to the evaluation model after the likelihood is subjected to a training evaluation model. The technical scheme disclosed by the invention is used for assisting language teaching, in particular teaching of Chinese for foreigners, by which the language learning requirements of students are met. In addition, by adoption of the method and the device, the bias error in voice rhythms of students can be found in time and effective feedbacks are provided to the students, so that the language learning efficiency of the students are improved; and the method and the device are particularly beneficial for Japanese students to learn Chinese.

Description

technical field [0001] The invention relates to the field of speech recognition, in particular to a speech evaluation method and device based on pronunciation rhythm. Background technique [0002] In daily life, it is not difficult to find such a phenomenon: Japanese students' Chinese pronunciation rhythm is often influenced by their mother tongue, which is very different from that of Chinese native speakers. And studies have shown that for Japanese learners, the most difficult part is the learning of spoken Chinese. If we can find out the mistakes in Japanese students' Chinese pronunciation rhythm in time and give them effective feedback, it will greatly improve their oral Chinese learning efficiency. [0003] However, with the further heating up of the Chinese language, the number of people learning Chinese is increasing sharply. Traditional teaching resources are limited, and the errors in students' Chinese pronunciation rhythm cannot be found in time, so they cannot mee...

AI Technical Summary

Problems solved by technology

[0003] However, with the further heating up of the Chinese language, the number of people learning Chinese is increasing sharply. Traditional teaching resources are limited, and the errors in students' Chinese pronunciation rhythm cannot be found in time, so they cannot meet the needs of students.

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