2017
EMNLP
EMNLP 2017
Syllable-aware Neural Language Models: A Failure to Beat Character-aware Ones
Abstract
AbstractSyllabification does not seem to improve word-level RNN language modeling quality when compared to character-based segmentation. However, our best syllable-aware language model, achieving performance comparable to the competitive character-aware model, has 18%-33% fewer parameters and is trained 1.2-2.2 times faster.
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Interdisciplinary Bridge
- Deep Learning and Natural Language Processing
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Trend Setter
- Language Models
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Keyword Pioneer
- rnn language model
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Hot Topic Early Bird
- neural language model
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Cross-Pollinator
- Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio