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20 papers · 2 filters
Sentence-wise Smooth Regularization for Sequence to Sequence Learning
Chengyue Gong, Xu Tan, Di He +1
Maximum-likelihood estimation (MLE) is widely used in sequence to sequence tasks for model training. It uniformly treats the generation/prediction of each target token as multi-cla…
Text Morphing
Shaohan Huang, Yu Wu, Furu Wei +1
In this paper, we introduce a novel natural language generation task, termed as text morphing, which targets at generating the intermediate sentences that are fluency and smooth wi…
Attention-Guided Answer Distillation for Machine Reading Comprehension
Minghao Hu, Yuxing Peng, Furu Wei +4
Despite that current reading comprehension systems have achieved significant advancements, their promising performances are often obtained at the cost of making an ensemble of nume…
Neural Melody Composition from Lyrics
Hangbo Bao, Shaohan Huang, Furu Wei +5
In this paper, we study a novel task that learns to compose music from natural language. Given the lyrics as input, we propose a melody composition model that generates lyrics-cond…
Knowledge-Aware Conversational Semantic Parsing Over Web Tables
Yibo Sun, Duyu Tang, Nan Duan +3
Conversational semantic parsing over tables requires knowledge acquiring and reasoning abilities, which have not been well explored by current state-of-the-art approaches. Motivate…
Neural Speech Synthesis with Transformer Network
Naihan Li, Shujie Liu, Yanqing Liu +3
Although end-to-end neural text-to-speech (TTS) methods (such as Tacotron2) are proposed and achieve state-of-the-art performance, they still suffer from two problems: 1) low effic…