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[2022-08-15] 오늘의 자연어처리 Assessing the Unitary RNN as an End-to-End Compositional Model of Syntax We show that both an LSTM and a unitary-evolution recurrent neural network (URN) can achieve encouraging accuracy on two types of syntactic patterns: context-free long distance agreement, and mildly context-sensitive cross serial dependencies. This work extends recent experiments on deeply nested context-free long distance .. 2022. 8. 15.
[2022-08-15] 오늘의 자연어처리 Speech Synthesis with Mixed Emotions Emotional speech synthesis aims to synthesize human voices with various emotional effects. The current studies are mostly focused on imitating an averaged style belonging to a specific emotion type. In this paper, we seek to generate speech with a mixture of emotions at run-time. We propose a novel formulation that measures the relative difference between the.. 2022. 8. 15.
[2022-08-15] 오늘의 자연어처리 RealityTalk: Real-Time Speech-Driven Augmented Presentation for AR Live Storytelling We present RealityTalk, a system that augments real-time live presentations with speech-driven interactive virtual elements. Augmented presentations leverage embedded visuals and animation for engaging and expressive storytelling. However, existing tools for live presentations often lack interactivity and improv.. 2022. 8. 15.
[2022-08-11] 오늘의 자연어처리 CLEVR-Math: A Dataset for Compositional Language, Visual and Mathematical Reasoning We introduce CLEVR-Math, a multi-modal math word problems dataset consisting of simple math word problems involving addition/subtraction, represented partly by a textual description and partly by an image illustrating the scenario. The text describes actions performed on the scene that is depicted in the image. S.. 2022. 8. 11.
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