add support for normalizing flow emission model for HMM
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 1k
- Forks
- 114
- Avg merge
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- Merged PRs (30d)
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Description
Then try to replicate this cool application, where they did unsupervised POS discovery from penn treebank text corpus, using fixed word embeddings as the observaiton sequence.
J. He, G. Neubig, and T. Berg-Kirkpatrick, “Unsupervised Learning of Syntactic Structure with Invertible Neural Projections,” in EMNLP, 2018 [Online]. Available: http://arxiv.org/abs/1808.09111
Contributor guide
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 by reading the cited EMNLP 2018 paper and the existing HMM emission-model interfaces. The issue names no files or tests; done would mean supporting a normalizing-flow emission model and reproducing the paper's unsupervised POS discovery experiment on Penn Treebank text with fixed word embeddings.
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
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100