Segment segmentation detection method and system, spoken language evaluation method and system

Abstract

The invention discloses a segment segmentation detection method and system, the method comprising: obtaining the segment segmentation result obtained by segmenting the reading voice; performing voice recognition on the reading voice to obtain the recognition result; according to the The reading text corresponding to the reading voice calculates the recognition rate of the segmentation result and the recognition rate of the recognition result respectively; if the recognition rate of the segmentation result is higher than the recognition rate of the recognition result, then determine that the segmentation result is normal; otherwise It is determined that the segmentation result is abnormal. The invention also discloses a spoken language evaluation method and system. The present invention can effectively detect whether the segment segmentation result is abnormal, thereby ensuring the accuracy of the evaluation result.

Description

technical field [0001] The invention relates to the technical field of speech signal processing, in particular to a segment segmentation detection method and system, and a spoken language evaluation method and system. Background technique [0002] Spoken language evaluation can realize the evaluation of the speaker's speaking level, and guide the speaker to learn according to the evaluation results. The basic principle of evaluation comes from measuring the difference between standard pronunciation and actual pronunciation. Segment segmentation is a mainstream method in oral language evaluation technology. The specific process is: build a decoding network based on the reading text, and analyze the acoustic features of the speech based on The decoding network and the acoustic model are forced to align, and the result of segment segmentation is obtained by decoding. [0003] Such as figure 1 Shown is a flow chart of the traditional oral evaluation method, including the follo...

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Problems solved by technology

[0010] In the actual oral evaluation process of the above-mentioned traditional oral evaluation method, the following situations are likely to occur: the user does not read aloud according to the order of the text, the user reads content that has nothing to do with the text, or the environment is noisy. When these situations occur, it will lead to The segment segmentation boundary obtained is likely to be abnormal (or incorrect), and the subsequent evaluation process is based on the abnormal segment segmentation boundary, which will make the final output evaluation result unreliable and reduce the evaluation performance. The effect and user experience cannot meet the needs of users

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