{ "info": { "author": "Quan Wang", "author_email": "quanw@google.com", "bugtrack_url": null, "classifiers": [ "License :: OSI Approved :: Apache Software License", "Operating System :: OS Independent", "Programming Language :: Python :: 3" ], "description": "# SimpleDER [![Build Status](https://travis-ci.org/wq2012/SimpleDER.svg?branch=master)](https://travis-ci.org/wq2012/SimpleDER) [![PyPI Version](https://img.shields.io/pypi/v/simpleder.svg)](https://pypi.python.org/pypi/simpleder) [![Python Versions](https://img.shields.io/pypi/pyversions/simpleder.svg)](https://pypi.org/project/simpleder) [![Documentation](https://img.shields.io/badge/api-reference-blue.svg)](https://wq2012.github.io/SimpleDER)\n\n## Overview\n\nThis is a lightweight library to compute Diarization Error Rate (DER).\n\nFeatures **NOT** supported:\n\n* Handling overlapped speech, *i.e.* two speakers speaking at the same time.\n* Allowing segment boundary tolerance, *a.k.a.* the `collar` value.\n\nFor more sophisticated metrics with these supports, please use\n[pyannote-metrics](https://github.com/pyannote/pyannote-metrics) instead.\n\nTo learn more about speaker diarization, here is a curated list of resources:\n[awesome-diarization](https://github.com/wq2012/awesome-diarization).\n\n## Diarization Error Rate\n\nDiarization Error Rate (DER) is the most commonly used metrics for\n[speaker diarization](https://en.wikipedia.org/wiki/Speaker_diarisation).\n\nIts strict form is:\n\n```\n False Alarm + Miss + Overlap + Confusion\nDER = ------------------------------------------\n Reference Length\n```\n\nThe definition of each term:\n\n* `Reference Length:` The total length of the reference (ground truth).\n* `False Alarm`: Length of segments which are considered as speech in\n hypothesis, but not in reference.\n* `Miss`: Length of segments which are considered as speech in\n reference, but not in hypothesis.\n* `Overlap`: Length of segments which are considered as overlapped speech\n in hypothesis, but not in reference.\n **This library does NOT support overlap.**\n* `Confusion`: Length of segments which are assigned to different speakers\n in hypothesis and reference (after applying an optimal assignment).\n\nThe unit of each term is *seconds*.\n\nNote that DER can theoretically be larger than 1.0.\n\nReferences:\n\n* [pyannote-metrics documentation](https://pyannote.github.io/pyannote-metrics/reference.html)\n* [Xavier Anguera's thesis](http://www.xavieranguera.com/phdthesis/node108.html)\n\n## Tutorial\n\n### Install\n\nInstall the package by:\n\n```bash\npip3 install simpleder\n```\n\nor\n\n```bash\npython3 -m pip install simpleder\n```\n\n### API\n\nHere is a minimal example:\n\n```python\nimport simpleder\n\n# reference (ground truth)\nref = [(\"A\", 0.0, 1.0),\n (\"B\", 1.0, 1.5),\n (\"A\", 1.6, 2.1)]\n\n# hypothesis (diarization result from your algorithm)\nhyp = [(\"1\", 0.0, 0.8),\n (\"2\", 0.8, 1.4),\n (\"3\", 1.5, 1.8),\n (\"1\", 1.8, 2.0)]\n\nerror = simpleder.DER(ref, hyp)\n\nprint(\"DER={:.3f}\".format(error))\n```\n\nThis should output:\n\n```\nDER=0.350\n```\n\n", "description_content_type": "text/markdown", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/wq2012/SimpleDER", "keywords": "", "license": "", "maintainer": "", "maintainer_email": "", "name": "simpleder", "package_url": "https://pypi.org/project/simpleder/", "platform": "", "project_url": "https://pypi.org/project/simpleder/", "project_urls": { "Homepage": "https://github.com/wq2012/SimpleDER" }, "release_url": "https://pypi.org/project/simpleder/0.0.2/", "requires_dist": null, "requires_python": "", "summary": "A lightweight library to compute Diarization Error Rate (DER).", "version": "0.0.2" }, "last_serial": 4746480, "releases": { "0.0.1": [ { "comment_text": "", "digests": { "md5": "1e5652d54e04313c67fd47dd61a985d5", "sha256": 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