kaldingram
kaldingram provides Python and CLI tools to:
- train Kneser-Ney back-off n-gram language models in ARPA format
- entropy-prune ARPA language models
The implementation is based on Kaldi WSJ scripts and matches SRILM-style behavior.
Install
pip install kaldingram
CLI Usage
Train an n-gram LM
kaldingram train --ngram-order 4 --text corpus.txt --lm 4gram.arpa
Or stream text from stdin and write ARPA to stdout:
cat corpus.txt | kaldingram train --ngram-order 3 > 3gram.arpa
Prune an n-gram LM
kaldingram prune --threshold 1e-8 --lm 4gram.arpa --write-lm 4gram_pruned.arpa
Evaluate perplexity
kaldingram ppl --lm 4gram.arpa --text test.txt
cat test.txt | kaldingram ppl --lm 4gram.arpa
Development
Build package locally:
python -m pip install --upgrade build
python -m build
1 maintainer
Metadata
1 maintainer
Release files for kaldingram 0.1.2
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