Representing Movie Characters in Dialogues
| Autor: | Jia Deng, Mahmoud Azab, Noriyuki Kojima, Rada Mihalcea |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
business.industry Matrix (music) 02 engineering and technology 010501 environmental sciences computer.software_genre 01 natural sciences Conjunction (grammar) Character (mathematics) 0202 electrical engineering electronic engineering information engineering Question answering Embedding Encoding (semiotics) 020201 artificial intelligence & image processing Word2vec Artificial intelligence Representation (mathematics) business computer Natural language processing 0105 earth and related environmental sciences |
| Zdroj: | CoNLL |
| DOI: | 10.18653/v1/k19-1010 |
| Popis: | We introduce a new embedding model to represent movie characters and their interactions in a dialogue by encoding in the same representation the language used by these characters as well as information about the other participants in the dialogue. We evaluate the performance of these new character embeddings on two tasks: (1) character relatedness, using a dataset we introduce consisting of a dense character interaction matrix for 4,378 unique character pairs over 22 hours of dialogue from eighteen movies; and (2) character relation classification, for fine- and coarse-grained relations, as well as sentiment relations. Our experiments show that our model significantly outperforms the traditional Word2Vec continuous bag-of-words and skip-gram models, demonstrating the effectiveness of the character embeddings we introduce. We further show how these embeddings can be used in conjunction with a visual question answering system to improve over previous results. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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