Tan Yanxin


2021

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Category-Based Strategy-Driven Question Generator for Visual Dialogue
Shi Yanan | Tan Yanxin | Feng Fangxiang | Zheng Chunping | Wang Xiaojie
Proceedings of the 20th Chinese National Conference on Computational Linguistics

“GuessWhat?! is a task-oriented visual dialogue task which has two players a guesser and anoracle. Guesser aims to locate the object supposed by oracle by asking several Yes/No questions which are answered by oracle. How to ask proper questions is crucial to achieve the final goal of the whole task. Previous methods generally use an word-level generator which is hard to grasp the dialogue-level questioning strategy. They often generate repeated or useless questions. This paper proposes a sentence-level category-based strategy-driven question generator(CSQG) to explicitly provide a category based questioning strategy for the generator. First we encode the image and the dialogue history to decide the category of the next question to be generated. Thenthe question is generated with the helps of category-based dialogue strategy as well as encoding of both the image and dialogue history. The evaluation on large-scale visual dialogue dataset GuessWhat?! shows that our method can help guesser achieve 51.71% success rate which is the state-of-the-art on the supervised training methods.”