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Latent Semantics of Action Verbs Reflect Phonetic Parameters of Intensity and Emotional Content

机译:动作动词的潜在语义反映了强度和情感内容的语音参数

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Conjuring up our thoughts, language reflects statistical patterns of word co-occurrences which in turn come to describe how we perceive the world. Whether counting how frequently nouns and verbs combine in Google search queries, or extracting eigenvectors from term document matrices made up of Wikipedia lines and Shakespeare plots, the resulting latent semantics capture not only the associative links which form concepts, but also spatial dimensions embedded within the surface structure of language. As both the shape and movements of objects have been found to be associated with phonetic contrasts already in toddlers, this study explores whether articulatory and acoustic parameters may likewise differentiate the latent semantics of action verbs. Selecting 3 × 20 emotion-, face-, and hand-related verbs known to activate premotor areas in the brain, their mutual cosine similarities were computed using latent semantic analysis LSA, and the resulting adjacency matrices were compared based on two different large scale text corpora: HAWIK and TASA. Applying hierarchical clustering to identify common structures across the two text corpora, the verbs largely divide into combined mouth and hand movements versus emotional expressions. Transforming the verbs into their constituent phonemes, and projecting them into an articulatory space framed by tongue height and formant frequencies, the clustered small and large size movements appear differentiated by front versus back vowels corresponding to increasing levels of arousal. Whereas the clustered emotional verbs seem characterized by sequences of close versus open jaw produced phonemes, generating up- or downwards shifts in formant frequencies that may influence their perceived valence. Suggesting, that the latent semantics of action verbs reflect parameters of intensity and emotional polarity that appear correlated with the articulatory contrasts and acoustic characteristics of phonemes.
机译:令人联想起我们的思想,语言反映了单词共现的统计模式,进而描述了我们如何看待世界。无论是计算名词和动词在Google搜索查询中的组合频率,还是从由Wikipedia线和莎士比亚图组成的术语文档矩阵中提取特征向量,生成的潜在语义不仅捕获形成概念的关联链接,而且还捕获嵌入到概念中的空间维度。语言的表面结构。由于已经发现对象的形状和运动都已经与幼儿的语音对比相关联,因此本研究探讨了发音和声学参数是否同样可以区分动作动词的潜在语义。选择3×20个已知的可激活大脑前运动区的情绪,面部和手部相关动词,并使用潜在语义分析LSA计算它们的余弦相似度,并基于两个不同的大型文本比较所形成的邻接矩阵语料库:HAWIK和TASA。通过使用层次聚类来识别两个文本语料库中的通用结构,这些动词在很大程度上分为嘴巴和手部动作与情感表达的组合。将动词转换成它们的组成音素,并将它们投射到由舌头高度和共振峰频率构成的发音空间中,簇状的大小运动分别由前元音和后元音来区分,这与唤醒水平的提高相对应。而聚集的情感动词似乎具有下颚和下颚产生的音素序列的特征,共振峰频率产生向上或向下的移位,这可能会影响其感知价。这表明动作动词的潜在语义反映了强度和情绪极性的参数,这些参数似乎与音素的发音对比和声学特征相关。

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