TF-LM: TensorFlow-based Language Modeling Toolkit

LREC(2018)

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摘要
Recently, an abundance of deep learning toolkits has been made freely available. These toolkits typically offer the building blocks and sometimes simple example scripts, but designing and training a model still takes a considerable amount of time and knowledge. We present language modeling scripts based on TensorFlow that allow one to train and test competitive models directly, by using a pre-defined configuration or changing it to their needs. There are several options for input features (words, characters, words combined with characters, character n-grams) and for batching (sentence- or discourse-level). The models can be used to test the perplexity, predict the next word(s), re-score hypotheses or generate debugging files for interpolation with n-gram models. Additionally, we make available LSTM language models trained on a variety of Dutch texts and English benchmarks, that can be used immediately, thereby avoiding the time and computationally expensive training process.
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关键词
language modeling, LSTM, deep learning, toolkit
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