rsennrich/subword-nmt
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Rico Sennrich 2016-06-01 14:49:14 +01:00
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README.md
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@ -29,6 +29,6 @@ PUBLICATIONS
The segmentation methods are described in: The segmentation methods are described in:
Rico Sennrich, Barry Haddow and Alexandra Birch (2015): Rico Sennrich, Barry Haddow and Alexandra Birch (2016):
Neural Machine Translation of Rare Words with Subword Units Neural Machine Translation of Rare Words with Subword Units
http://arxiv.org/abs/1508.07909 Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL 2016). Berlin, Germany.

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apply_bpe.py
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@ -7,7 +7,8 @@ The text will not be smaller, but use only a fixed vocabulary, with rare words
encoded as variable-length sequences of subword units. encoded as variable-length sequences of subword units.
Reference: Reference:
Rico Sennrich, Barry Haddow and Alexandra Birch (2015). Neural Machine Translation of Rare Words with Subword Units. Rico Sennrich, Barry Haddow and Alexandra Birch (2016). Neural Machine Translation of Rare Words with Subword Units.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL 2016). Berlin, Germany.
""" """
from __future__ import unicode_literals, division from __future__ import unicode_literals, division

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bpe_toy.py
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@ -9,7 +9,8 @@ This is an (inefficient) toy implementation that shows the algorithm. For proces
indexing and incremental updates can be used to speed up the implementation (see learn_bpe.py). indexing and incremental updates can be used to speed up the implementation (see learn_bpe.py).
Reference: Reference:
Rico Sennrich, Barry Haddow and Alexandra Birch (2015). Neural Machine Translation of Rare Words with Subword Units. Rico Sennrich, Barry Haddow and Alexandra Birch (2016). Neural Machine Translation of Rare Words with Subword Units.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL 2016). Berlin, Germany.
""" """

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learn_bpe.py
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@ -7,7 +7,8 @@ Unlike the original BPE, it does not compress the plain text, but can be used to
of a text to a configurable number of symbols, with only a small increase in the number of tokens. of a text to a configurable number of symbols, with only a small increase in the number of tokens.
Reference: Reference:
Rico Sennrich, Barry Haddow and Alexandra Birch (2015). Neural Machine Translation of Rare Words with Subword Units. Rico Sennrich, Barry Haddow and Alexandra Birch (2016). Neural Machine Translation of Rare Words with Subword Units.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL 2016). Berlin, Germany.
""" """
from __future__ import unicode_literals from __future__ import unicode_literals