Representing Movie Characters in Dialogues
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.
Code (0)
등록된 구현이 없습니다.
Tasks
Question AnsweringRelation ClassificationVisual Question AnsweringVisual Question Answering (VQA)Similar Papers 제목 키워드 기반
Linguistic analysis of differences in portrayal of movie characters
We examine differences in portrayal of characters in movies using psycholinguistic and graph theoretic measures computed directly from screenplays. Differences are examined with respect to characters{'} gender, race, age…
regressionIdentifying gender bias in blockbuster movies through the lens of machine learning
The problem of gender bias is highly prevalent and well known. In this paper, we have analysed the portrayal of gender roles in English movies, a medium that effectively influences society in shaping people's beliefs and…
Movienet: A Movie Multilayer Network Model using Visual and Textual Semantic Cues
Discovering content and stories in movies is one of the most important concepts in multimedia content research studies. Network models have proven to be an efficient choice for this purpose. When an audience watches a mo…
Learning Video Context as Interleaved Multimodal Sequences
Narrative videos, such as movies, pose significant challenges in video understanding due to their rich contexts (characters, dialogues, storylines) and diverse demands (identify who, relationship, and reason). In this pa…
Language ModelingLanguage ModellingQuestion AnsweringText Retrieval+5Emotion Dynamics in Movie Dialogues
Emotion dynamics is a framework for measuring how an individual's emotions change over time. It is a powerful tool for understanding how we behave and interact with the world. In this paper, we introduce a framework to t…