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- W4225441479 abstract "Movie question answering, or MovieQA is a multimedia related task wherein one is provided with a video, the subtitle information, a question and candidate answers for it. The task is to predict the correct answer for the question using the components of the multimedia - namely video/images, audio and text. Traditionally, MovieQA is done using the image and text component of the multimedia. In this paper, we propose a novel network with triple-attention architecture for the inclusion of audio in the Movie QA task. This architecture is fashioned after a traditional dual attention network focused only on video and text. Experiments show that the inclusion of audio using the triple-attention network results provides complementary information for Movie QA task which is not captured by visual or textual component in the data. Experiments with a wide range of audio features show that using such a network can indeed improve MovieQA performance by about 7% relative to just using only visual features." @default.
- W4225441479 created "2022-05-05" @default.
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- W4225441479 date "2021-11-18" @default.
- W4225441479 modified "2023-09-24" @default.
- W4225441479 title "Triple Attention Network architecture for MovieQA" @default.
- W4225441479 hasPublicationYear "2021" @default.
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