TheanoLM - An Extensible Toolkit for Neural Network Language Modeling

May 03, 2016 ยท Declared Dead ยท ๐Ÿ› Proc. Interspeech 2016, pp. 3052-3056

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Authors Seppo Enarvi, Mikko Kurimo arXiv ID 1605.00942 Category cs.CL: Computation & Language Cross-listed cs.NE Citations 0 Venue Proc. Interspeech 2016, pp. 3052-3056 Last Checked 5 months ago
Abstract
We present a new tool for training neural network language models (NNLMs), scoring sentences, and generating text. The tool has been written using Python library Theano, which allows researcher to easily extend it and tune any aspect of the training process. Regardless of the flexibility, Theano is able to generate extremely fast native code that can utilize a GPU or multiple CPU cores in order to parallelize the heavy numerical computations. The tool has been evaluated in difficult Finnish and English conversational speech recognition tasks, and significant improvement was obtained over our best back-off n-gram models. The results that we obtained in the Finnish task were compared to those from existing RNNLM and RWTHLM toolkits, and found to be as good or better, while training times were an order of magnitude shorter.
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