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        "author": "Ben Lambert",
        "author_email": "blambert@gmail.com",
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        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Environment :: Console",
            "License :: OSI Approved :: Apache Software License",
            "Programming Language :: Python",
            "Topic :: Scientific/Engineering :: Artificial Intelligence",
            "Topic :: Text Processing",
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        "description": "asr_evaluation\n==============\n[![Build Status](https://travis-ci.org/belambert/asr-evaluation.svg?branch=master)](https://travis-ci.org/belambert/asr-evaluation)\n[![PyPI version](https://badge.fury.io/py/asr_evaluation.svg)](https://badge.fury.io/py/asr_evaluation)\n[![codecov](https://codecov.io/gh/belambert/asr-evaluation/branch/master/graph/badge.svg)](https://codecov.io/gh/belambert/asr-evaluation)\n\nPython module for evaluting ASR hypotheses (i.e. word error rate and word \nrecognition rate).\n\nThis module depends on the [editdistance](https://github.com/belambert/edit-distance)\nproject, for computing edit distances between arbitrary sequences.\n\nThe formatting of the output of this program is very loosely based around the \nsame idea as the align.c program commonly used within the Sphinx ASR community. \nThis may run a bit faster if neither instances nor confusions are printed.\n\nPlease let me know if you have any comments, questions, or problems.\n\nOutput\n------\nThe program outputs three standard measurements:\n - [Word error rate (WER)](https://en.wikipedia.org/wiki/Word_error_rate)\n - Word recognition rate (the number of _matched_ words in the alignment divided by the number of words in the reference).\n - Sentence error rate (SER) (the number of incorrect sentences divided by the total number of sentences).\n\n\nInstalling & uninstalling\n-------------------------\nThe easiest way to install is using pip:\n\n    pip install asr-evaluation\n\nAlternatively you can clone this git repo and install using distutils:\n\n    git clone git@github.com:belambert/asr-evaluation.git\n    cd asr-evaluation\n    python setup.py install\n\nTo uninstall with pip:\n\n    pip uninstall asr-evaluation\n\n\nCommand line usage\n------------------\nFor command line usage, see:\n```\n    wer --help\n```\n\nIt should display something like this:\n\n```    \nusage: wer [-h] [-i | -r] [--head-ids] [-id] [-c] [-p] [-m count] [-a] [-e]\n           ref hyp\n\nEvaluate an ASR transcript against a reference transcript.\n\npositional arguments:\n  ref                   Reference transcript filename\n  hyp                   ASR hypothesis filename\n\noptional arguments:\n  -h, --help            show this help message and exit\n  -i, --print-instances\n                        Print all individual sentences and their errors.\n  -r, --print-errors    Print all individual sentences that contain errors.\n  --head-ids            Hypothesis and reference files have ids in the first\n                        token? (Kaldi format)\n  -id, --tail-ids, --has-ids\n                        Hypothesis and reference files have ids in the last\n                        token? (Sphinx format)\n  -c, --confusions      Print tables of which words were confused.\n  -p, --print-wer-vs-length\n                        Print table of average WER grouped by reference\n                        sentence length.\n  -m count, --min-word-count count\n                        Minimum word count to show a word in confusions.\n  -a, --case-insensitive\n                        Down-case the text before running the evaluation.\n  -e, --remove-empty-refs\n                        Skip over any examples where the reference is empty.\n```\n\nContributing and code of conduct\n--------------------------------\nFor contributions, it's best to Github issues and pull requests. Proper\ntesting and documentation suggested.\n\nCode of conduct is expected to be reasonable, especially as specified by\nthe [Contributor Covenant](http://contributor-covenant.org/version/1/4/)\n\n\n",
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