Image-based Natural Language Understanding Using 2D Convolutional Neural Networks

24 Oct 2018Erinc MerdivanAnastasios VafeiadisDimitrios KalatzisSten HankeJohannes KropfKonstantinos VotisDimitrios GiakoumisDimitrios TzovarasLiming ChenRaouf HamzaouiMatthieu Geist

We propose a new approach to natural language understanding in which we consider the input text as an image and apply 2D Convolutional Neural Networks to learn the local and global semantics of the sentences from the variations ofthe visual patterns of words. Our approach demonstrates that it is possible to get semantically meaningful features from images with text without using optical character recognition and sequential processing pipelines, techniques that traditional Natural Language Understanding algorithms require... (read more)

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