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Update README_English.md
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---
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license: mit
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language:
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- gl
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metrics:
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- bleu (Gold1): 79.6
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- bleu (Gold2): 43.3
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- bleu (Flores): 21.8
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- bleu (Test-suite): 74.3
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---
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**Model description**
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Model developed with OpenNMT for the Spanish-Galician pair using a transformer architecture.
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**How to translate**
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+ Open bash terminal
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+ Install [Python 3.9](https://www.python.org/downloads/release/python-390/)
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+ Install [Open NMT toolkit v.2.2](https://github.com/OpenNMT/OpenNMT-py)
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+ Translate an input_text using the NOS-MT-en-gl model with the following command:
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```bash
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onmt_translate -src input_text -model NOS-MT-es-gl -output ./output_file.txt -replace_unk -phrase_table phrase_table-es-gl.txt -gpu 0
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```
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+ The result of the translation will be in the PATH indicated by the -output flag.
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**Training**
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In the training we have used authentic and synthetic corpora from [ProxectoNós](https://github.com/proxectonos/corpora). The former are corpora of translations directly produced by human translators. The latter are corpora of spanish-portuguese translations, which we have converted into spanish-galician by means of portuguese-galician translation with Opentrad/Apertium and transliteration for out-of-vocabulary words.
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**Training process**
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+ Tokenization of the datasets made with linguakit tokeniser https://github.com/citiususc/Linguakit
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+ Vocabulary for the models was created by the script [learn_bpe.py](https://github.com/OpenNMT/OpenNMT-py/blob/master/tools/learn_bpe.py) da open NMT
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+ Using the .yaml in this repository you can replicate the training process as follows
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```bash
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onmt_build_vocab -config bpe-es-gl_emb.yaml -n_sample 100000
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onmt_train -config bpe-es-gl_emb.yaml
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```
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**Hyper-parameters**
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The parameters used for the development of the model can be directly viewed in the same .yaml file bpe-es-gl_emb.yaml
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**Evaluation**
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The BLEU evaluation of the models is done by mixing internally developed tests (gold1, gold2, test-suite) with other datasets available in Galician (Flores).
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| GOLD 1 | GOLD 2 | FLORES | TEST-SUITE|
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| ------------- |:-------------:| -------:|----------:|
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| 79.6 | 43.3 | 21.8 | 74.3 |
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**Licensing information**
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MIT License
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Copyright (c) 2023 Proxecto Nós
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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**Funding**
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This research was funded by the project "Nós: Galician in the society and economy of artificial intelligence", agreement between Xunta de Galicia and University of Santiago de Compostela, and grant ED431G2019/04 by the Galician Ministry of Education, University and Professional Training, and the European Regional Development Fund (ERDF/FEDER program), and Groups of Reference: ED431C 2020/21.
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**Citation Information**
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