Exploring Dialogism Using Language Models
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| Title: | Exploring Dialogism Using Language Models |
|---|---|
| Language: | English |
| Authors: | Ruseti, Stefan, Dascalu, Maria-Dorinela, Corlatescu, Dragos-Georgian, Dascalu, Mihai, Trausan-Matu, Stefan, McNamara, Danielle S. |
| Source: | Grantee Submission. 2021Paper presented at the International Conference on Artificial Intelligence in Education (AIED) (2021). |
| Peer Reviewed: | Y |
| Page Count: | 6 |
| Publication Date: | 2021 |
| Sponsoring Agency: | Institute of Education Sciences (ED) Office of Naval Research (ONR) (DOD) |
| Contract Number: | R305A180144 R305A180261 N000141712300 N000142012623 |
| Document Type: | Speeches/Meeting Papers Reports - Research |
| Descriptors: | Dialogs (Language), Computational Linguistics, Semantics, Models, Form Classes (Languages), Scores, Visual Aids |
| DOI: | 10.1007/978-3-030-78270-2_53 |
| Abstract: | Dialogism is a philosophical theory centered on the idea that life involves a dialogue among multiple voices in a continuous exchange and interaction. Considering human language, different ideas or points of view take the form of voices, which spread throughout any discourse and influence it. From a computational point of view, voices can be operationalized as semantic chains that contain related words. This study introduces and evaluates a novel method of identifying semantic chains using BERT, a state-of-the-art language model for computational linguistics. The resulting model generalizes to multiple relations including repetitions, semantically related concepts from WordNet (i.e., synonyms, hypernyms, hyponyms, and siblings), as well as pronominal resolutions. By combining the attention scores between words, word pairs are merged into connected components that denote emerging voices from the discourse. The introduced visualization argues for a more dense capturing of inner semantic links between words and even compound words in contrast to classical methods of building lexical chains. [This paper was published in: "AIED 2021," edited by I. Roll et al., Springer Nature Switzerland AG, 2021, pp. 296-301.] |
| Abstractor: | As Provided |
| IES Funded: | Yes |
| Entry Date: | 2022 |
| Accession Number: | ED619754 |
| Database: | ERIC |
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