This is the Windows app named UnsupervisedMT whose latest release can be downloaded as UnsupervisedMTsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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ເຫຼົ້າແວງເປັນວິທີການແລ່ນຊອບແວ Windows ໃນ Linux, ແຕ່ບໍ່ມີ Windows ທີ່ຕ້ອງການ. ເຫຼົ້າແວງແມ່ນຊັ້ນຄວາມເຂົ້າກັນໄດ້ຂອງ Windows ແຫຼ່ງເປີດທີ່ສາມາດເອີ້ນໃຊ້ໂຄງການ Windows ໂດຍກົງໃນ desktop Linux ໃດກໍໄດ້. ໂດຍພື້ນຖານແລ້ວ, Wine ກໍາລັງພະຍາຍາມປະຕິບັດໃຫມ່ຢ່າງພຽງພໍຂອງ Windows ຕັ້ງແຕ່ເລີ່ມຕົ້ນເພື່ອໃຫ້ມັນສາມາດດໍາເນີນການຄໍາຮ້ອງສະຫມັກ Windows ທັງຫມົດໄດ້ໂດຍບໍ່ຕ້ອງໃຊ້ Windows.
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ບໍ່ມີການຄວບຄຸມMT
ລາຍລະອຽດ
Unsupervised Machine Translation is a research repository that implements both phrase-based SMT and neural MT approaches for translation without parallel corpora. The neural component supports multiple architectures—seq2seq, biLSTM with attention, and Transformer—and allows extensive parameter sharing across languages to improve data efficiency. Training relies on denoising auto-encoding and back-translation, with on-the-fly, multithreaded generation of synthetic parallel data to continually refresh supervision signals. The project also provides scripts to fetch and preprocess monolingual data, learn BPE codes, and train cross-lingual embeddings that bootstrap unsupervised alignment between languages. Beyond the core EMNLP 2018 setup, the codebase exposes additional, optional capabilities such as multi-language training, language model pretraining with shared parameters, and adversarial training.
ຄຸນລັກສະນະ
- Neural MT with seq2seq, biLSTM+attention, and Transformer architectures
- Parameter sharing across encoders/decoders and embeddings for multiple languages
- Denoising auto-encoder training and back-translation with on-the-fly generation
- Utilities to download, tokenize, BPE, and binarize large monolingual corpora
- Cross-lingual embeddings via fastText or alignment methods to initialize models
- Unsupervised PBSMT pipeline with automated Moses training and evaluation
ພາສາການຂຽນໂປຣແກຣມ
Python, Unix Shell
ປະເພດ
This is an application that can also be fetched from https://sourceforge.net/projects/unsupervisedmt.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.