An automatic scoring method for Chinese-English spoken translation based on attention LSTM

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2022-01-13 DOI:10.4108/eai.13-1-2022.172818

X. Guo

引用次数: 2

Abstract

In this paper, we propose an automatic scoring method for Chinese-English spoken translation based on attention LSTM. We select semantic keywords, sentence drift and spoken fluency as the main parameters of scoring. In order to improve the accuracy of keyword scoring, this paper uses synonym discrimination method to identify the synonyms in the examinees' answer keywords. At the sentence level, attention LSTM model is used to analyze examinees' translation of sentence general idea. Finally, spoken fluency is scored based on tempo/rate and speech distribution. The final translation quality score is obtained by combining the weighted scores of the three parameters. The experimental results show that the proposed method is in good agreement with the result of manual grading, and achieves the expected design goal compared with other methods.

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基于注意力LSTM的汉英口语翻译自动评分方法

本文提出了一种基于注意力LSTM的汉英口语翻译自动评分方法。我们选择语义关键词、句子漂移和口语流利度作为评分的主要参数。为了提高关键词评分的准确性，本文采用同义词辨析法对考生答案关键词中的同义词进行识别。在句子层面，使用注意力LSTM模型分析考生对句子大意的翻译。最后，口语流利度是根据语速/语速和语言分布来评分的。将三个参数的加权得分结合得到最终的翻译质量得分。实验结果表明，该方法与人工分级结果吻合较好，与其他方法相比达到了预期的设计目标。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.