Algorithm research of spoken English assessment based on fuzzy measure and speech recognition technology

Dongbo Cao, Ying Guo
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引用次数: 8

Abstract

At present, many speech recognition algorithms are difficult to effectively evaluate the fuzziness of the evaluation algorithm. Based on this, this dissertation uses the speech recognition technology based on fuzzy measure to evaluate the spoken English. In the study the fuzzy measure, based on the traditional algorithm, is used to evaluate the spoken English and different characteristic parameters are extracted to construct the corresponding evaluation model. Simultaneously, the pronunciation is evaluated through automatic learning rules. The English speaking assessment model based on fuzzy measure and speech recognition technology is constructed and validated. The research shows that compared with the traditional algorithms, the spoken language evaluation algorithm based on fuzzy measure and speech recognition technology has the incomparable superiority, and can provide a reference for the follow-up related research.
基于模糊度量和语音识别技术的英语口语评价算法研究
目前,许多语音识别算法都难以有效地对评价算法的模糊性进行评价。在此基础上,本文采用基于模糊度量的语音识别技术对英语口语进行评价。本研究在传统算法的基础上,采用模糊测度对英语口语进行评价,提取不同的特征参数,构建相应的评价模型。同时,通过自动学习规则对发音进行评估。建立了基于模糊度量和语音识别技术的英语口语评价模型并进行了验证。研究表明,与传统算法相比,基于模糊测度和语音识别技术的口语评价算法具有无可比拟的优势,可为后续相关研究提供参考。
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