Only training alignment model for marker placement on translated content
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- Dominant language
- Python
- Stars
- 39
- Forks
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- Avg merge
- 1d 9h
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Description
This issue also exists in machine.py/Serval: https://github.com/sillsdev/machine.py/issues/320. See there for more details.
This is slightly more complicated to fix here in silnlp since we'll have to supply training data to the postprocessor (or train the alignment model during training and reference it somehow in postprocessing) whereas in machine.py, we have access to the training and inference data in one place already.
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the linked machine.py/Serval issue 320 for the detailed behavior and compare its approach with silnlp's postprocessor. Determine how training data can be supplied to the postprocessor, or how a training-time alignment model can be referenced during postprocessing. Done means translated marker placement uses a trained alignment model in silnlp.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100