https://github.com/timedelta/submodularity-for-data-selection

Some old code I wrote around 2014 based on "Submodularity for Data Selection in Statistical Machine Translation"
https://github.com/timedelta/submodularity-for-data-selection

Last synced: about 2 months ago
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Some old code I wrote around 2014 based on "Submodularity for Data Selection in Statistical Machine Translation"

• Host: GitHub
• URL: https://github.com/timedelta/submodularity-for-data-selection
• Owner: TimeDelta
• Created: 2023-09-28T15:12:33.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2023-09-28T15:54:27.000Z (over 1 year ago)
• Last Synced: 2024-10-16T13:20:59.229Z (3 months ago)
• Language: Roff
• Size: 32.7 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
This is some old corpus augmentation code I wrote around 2014. The main algorithm is in [Filter.cpp](scripts/Filter.cpp), which is based on the paper [Submodularity for Data Selection in Statistical Machine Translation](https://aclanthology.org/D14-1014.pdf). There are also some supporting scripts for data prep, transforming the output to a WFST ([arpa2fst](scripts/arpa2fst)), the main mining script ([mine_google.py](scripts/mine_google.py)), etc.