This study explores how sentiment analysis, a natural language processing technique, can help to assess the accuracy of interpreting learners’ renditions. The data was obtained from a corpus consisting of 22 interpreting learners’ performance over a training period of 11 weeks and comparable professional interpreters’ performance used as a reference. The sentiment scores of learners’ output were calculated using two lexicon-based sentiment tools and compared to the reference. The results revealed the learners’ limited ability to convey the speaker’s sentiment, which mainly resulted from their omission and distortion of key sentiment words and their intensity. Additionally, statistically significant correlations were found between the learner-reference sentiment gap of a given rendition and its accuracy level as perceived by the human raters, yet the extent of correlation is moderate. This suggests that the predictive power of sentiment analysis as a standalone indicator of accuracy is limited. Overall, the findings of this study have practical implications for the design of automated interpreting quality assessment tools and interpreting training.

中文翻译：

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情感分析可以帮助评估口译的准确性吗？语料库辅助计算语言学方法


本研究探讨了情感分析（一种自然语言处理技术）如何帮助评估解释学习者演绎内容的准确性。数据来自一个语料库，该语料库由 22 名口译学习者在 11 周的培训期间的表现和用作参考的可比专业口译员的表现组成。学习者输出的情绪得分是使用两个基于词典的情绪工具计算的，并与参考进行比较。结果显示，学习者传达说话者情绪的能力有限，这主要是由于他们对关键情感词及其强度的遗漏和扭曲。此外，在给定再现的学习者-参考情感差距与人工评分者感知的准确性水平之间发现具有统计学意义的相关性，但相关性程度适中。这表明，情绪分析作为独立的准确性指标的预测能力是有限的。总体而言，本研究的结果对自动口译质量评估工具和口译培训的设计具有实际意义。