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license: MIT |
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language: gl (Galician) |
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metrics: |
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- bleu (Gold1): 36.8 |
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- bleu (Gold2): 47.1 |
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- bleu (Flores): 32.3 |
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- bleu (Test-suite): 42.7 |
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--- |
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License: MIT |
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--- |
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**Model Description** |
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OpenNMT model for English-Galician 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聽-model NOS-MT-en-gl -output ./output_file.txt -replace_unk -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 [ProxectoN贸s](https://github.com/proxectonos/corpora). The former are corpora of translations directly produced by human translators. The latter are corpora of English-Portuguese translations, which we have converted into English-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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+ The vocabulary for the models was generated through the script [learn_bpe.py](https://github.com/OpenNMT/OpenNMT-py/blob/master/tools/learn_bpe.py) of OpenNMT |
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+ Using .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-en-gl_emb.yaml -n_sample 100000 |
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onmt_train -config bpe-en-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 consulted in the same .yaml file bpe-en-gl_emb.yaml |
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**Evaluation** |
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The BLEU evaluation of the models is made with a mixture of internally developed tests (gold1, gold2, test-suite) and 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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| 36.8 | 47.1 | 32.3 | 42.7 | |
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**Licensing information** |
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MIT License |
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Copyright (c) 2023 Proxecto N贸s |
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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 "N贸s: 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** |