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Character-Word LSTM Language Models

Abstract · Apr 10, 2017 11:42 ·

character lms word lstm characters infrequent words character embedding cs-cl

Arxiv Abstract

  • Lyan Verwimp
  • Joris Pelemans
  • Hugo Van hamme
  • Patrick Wambacq

We present a Character-Word Long Short-Term Memory Language Model which both reduces the perplexity with respect to a baseline word-level language model and reduces the number of parameters of the model. Character information can reveal structural (dis)similarities between words and can even be used when a word is out-of-vocabulary, thus improving the modeling of infrequent and unknown words. By concatenating word and character embeddings, we achieve up to 2.77% relative improvement on English compared to a baseline model with a similar amount of parameters and 4.57% on Dutch. Moreover, we also outperform baseline word-level models with a larger number of parameters.

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