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Investigating Verbal Intelligence using the TF-IDF Approach

机译:使用TF-IDF方法调查言语智能

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In this paper we investigated differences in language use of speakers yielding different verbal intelligence when they describe the same event. The work is based on a corpus containing descriptions of a short film and verbal intelligence scores of the speakers. For analyzing the monologues and the film transcript, the number of reused words, lemmas, n-grams, cosine similarity and other features were calculated and compared to each other for different verbal intelligence groups. The results showed that the similarity of monologues of higher verbal intelligence speakers was greater than of lower and average verbal intelligence participants. A possible explanation of this phenomenon is that candidates yielding higher verbal intelligence have a better short-term memory. In this paper we also checked a hypothesis that differences in vocabulary of speakers yielding different verbal intelligence are sufficient enough for good classification results. For proving this hypothesis, the Nearest Neighbor classifier was trained using TF-IDF vocabulary measures. The maximum achieved accuracy was 92.86%.
机译:在本文中,我们在描述同一事件时调查了扬声器的语言使用差异。这项工作基于包含扬声器短片和口头智能分数的描述的语料库。为了分析独白和薄膜转录物,计算重复使用的单词,lemmas,n-gram,余弦相似度和其他特征,并彼此进行不同的言语智能组。结果表明,较高的言语情报演讲者的独白性的相似性大于较低和平均的言语情报参与者。这种现象的可能解释是候选人产生更高的言语智力,具有更好的短期记忆。在本文中,我们还检查了一个假设,即发言者的词汇量差异,产生不同的言语智能足以足以获得良好的分类结果。为了证明这一假设,使用TF-IDF词汇测量训练最近的邻居分类器。最大达到的准确度为92.86%。

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