belambert/asr-evaluation

Python module for evaluating ASR hypotheses (e.g. word error rate, word recognition rate).

49
/ 100
Emerging

Leverages edit distance algorithms to compute alignment-based metrics (WER, word recognition rate, sentence error rate) between reference and hypothesis transcripts. Supports multiple input formats including Kaldi and Sphinx conventions, with optional detailed output including confusion matrices and per-sentence error analysis. Built for integration with ASR pipelines and compatible with common speech recognition framework conventions.

283 stars. No commits in the last 6 months.

Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 23 / 25

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Stars

283

Forks

78

Language

Python

License

Apache-2.0

Last pushed

Aug 15, 2023

Commits (30d)

0

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