E mbodied BERT : Cognitively Informed Metaphor Detection Incorporating Sensorimotor Information (2024)

Abstract: The identification of metaphor is a crucial prerequisite for many downstream language tasks, such as sentiment analysis, opinion mining, and textual entailment. State-of-the-art systems of metaphor detection implement heuristic principles such as Metaphor Identification Procedure (MIP) and Selection Preference Violation (SPV). We propose an innovative approach that leverages the cognitive information of embodiment that can be derived from word embeddings, and explicitly models the process of sensorimotor change that has been demonstrated as essential for human metaphor processing. We showed that this cognitively motivated module is effective and can improve metaphor detection, compared with the heuristic MIP that has been applied previously.

## introduction metaphor is a common type of figurative language that allows communicators to express novel construal @xcite and convey a myriad of implicit meanings @xcite . effective metaphor processing is essential for natural language processing tasks @xcite , such as sentiment analysis, machine translation, and textual entailment. @xcite @xcite . as a result, nlp researchers have focused on the computational modeling of metaphor, which typically starts with the identification of metaphors. the state-of-the-art systems of metaphor identification typically rely on two heuristic principles: the metaphor identification procedure (mip) @xcite , and selection preference vi-olation (spv) @xcite . mip identifies metaphors by recognizing that a word's metaphorical meaning differs from its basic, 'more concrete', 'related to bodily action', and 'historically older' meaning @xcite . spv detects metaphors by identifying violations of words' semantic selection preferences in context. the modeling of mip usually begins with the extraction of basic and contextual representations of target words and then learns their general differences @xcite , while spv focuses on the relation between target words and their contexts @xcite . despite their effectiveness, they neglect the cognitive characteristics of metaphor. embodied cognition posits that all cognitive acts, including language processing, are rooted in perception and action @xcite . psycholinguistic evidence supports that metaphor processing is also embodied @xcite , but the contribution of embodiment is dynamic. specifically, the embodiment levels of a metaphorical word often changes compared to the word's literal meaning during the online processing @xcite . for example, in the metaphorical use of the verb 'drink' in (a), the embodied features of the action 'drink', such as 'consumed by mouth', and 'the object must be liquid' are abstracted away, unlike in its literal use in (b). this abstraction of sensorimotor information is essential for humans to derive a metaphorical sense of 'drink' (to consume a large amount quickly), especially in the early stage of a metaphor @xcite foot_0 . ## conclusion in this study, we contribute a cognitively motivated system for metaphor detection embodied-bert, which implements the idea that metaphorical words tend to show unique patterns of sensorimotor change in context. we have demonstrated quantitatively and qualitatively that incorporating the cognitive module mip_sm can lead to performance improvements over systems simply using mip. based on our results, we envision that the incorporation of embodiment information cannot only benefit metaphor detection, but also many other language understanding tasks that require embodied experience.