Changelog

Version 3.0.1 (2020-07-02)

  • setup: switch to pyannote.database 4.0+

Version 3.0 (2020-06-15)

  • feat: add DetectionCostFunction detection metric (@nryant)

  • BREAKING: rename pyannote-metrics.py CLI to pyannote-metrics

Version 2.3 (2020-02-26)

  • feat: add DetectionPrecisionRecallFMeasure compound metric (@MarvinLvn)

  • fix: fix corner “in f-measure” case when both precision and recall are zero (@MarvinLvn)

  • fix: fix a typo in documentation (@wq2012)

Version 2.2 (2019-12-13)

  • feat: add support for evaluation of overlapped speech detection

  • feat: setup continuous integration

  • setup: switch to pyannote.core 3.2

Version 2.1 (2019-06-24)

  • chore: rewrite mapping and matching routines

  • fix: remove buggy xarray dependency

  • setup: switch to pyannote.core 3.0

Version 2.0.2 (2019-04-15)

  • fix: avoid division by zero

Version 2.0.1 (2019-03-20)

  • BREAKING: drop support for all file formats but RTTM

  • BREAKING: drop Python 2.7 support

  • setup: switch to pyannote.database 2.0

  • setup: switch to pyannote.core 2.1

Version 1.8.1 (2018-11-19)

  • setup: switch to pyannote.core 2.0

Version 1.8 (2018-09-03)

  • feat: add compound segmentation metric SegmentationPurityCoverageFMeasure (@diego-fustes)

  • fix: fix typo in IdentificationErrorAnalysis (@benjisympa)

Version 1.7.1 (2018-09-03)

  • fix: fix broken images in documentation

Version 1.7 (2018-03-17)

  • feat: add option to filter out target trials in “spotting” mode

  • chore: default to “parallel=False”

Version 1.6.1 (2018-02-05)

  • fix: fix Diarization{Purity | Coverage} with empty references

  • improve: improve support for speaker spotting experiments

  • chore: (temporarily?) remove parallel processing in pyannote.metrics.py

  • setup: drop support for Python 2

Version 1.5 (2017-10-20)

  • feat: add fixed vs. variable latency switch for LLSS

Version 1.4.3 (2017-10-17)

  • fix: add more safety checks to pyannote-metrics.py “spotting” mode

  • setup: switch to pyannote.core 1.2, pyannote.database 1.1, pyannote.parser 0.7

Version 1.4.2 (2017-10-13)

  • improve: set latency of missed detections to maximum possible value

  • improve: improve instructions in pyannote-metrics.py –help

Version 1.4.1 (2017-10-02)

  • feat: add LowLatencySpeakerSpotting metric

  • feat: add “spotting” mode to pyannote-metrics.py

  • setup: switch to pyannote.database 1.0

Version 1.3 (2017-09-19)

  • feat: add “skip_overlap” option to not evaluate overlapping speech regions

  • improve: bring performance improvement to diarization metrics

  • fix: fix a bug where collar was applied twice in DiarizationErrorRate

  • fix: add collar support to purity/coverage/homogeneity/completeness

  • fix: fix a bug happening in ‘uemify’ when both reference and hypothesis are empty

  • fix: fix a “division by zero” error in homogeneity/completeness

  • setup: switch to pyannote.core 1.1 (major performance improvements)

Version 1.2 (2017-07-21)

  • feat: add method DiarizationPurityCoverageFMeasure.compute_metrics to get purity, coverage, and their F-measure (all at once)

Version 1.1 (2017-07-20)

  • feat: add new metric ‘DiarizationPurityCoverageFMeasure’

  • doc: update installation instructions

  • setup: switch to pyannote.core 1.0.4

Version 1.0 (2017-07-04)

  • setup: switch to pyannote.core 1.0

  • feat: add score calibration for binary classification tasks

  • doc: update citation

Version 0.14.4 (2017-03-27)

  • doc: update notebook to latest version

Version 0.14.3 (2017-03-27)

  • doc: add Sphinx documentation

Version 0.14.2 (2017-03-21)

  • feat: better README and technical report

Version 0.14.1 (2017-03-16)

  • chore: rename SegmentationError to SegmentationErrorAnalysis

  • fix: fix DetectionErrorRate support for kwargs

Version 0.14 (2017-02-06)

  • feat: add “parallel” option to not use multiprocessing

  • feat: add “accuracy” in “detection” report

  • setup: switch to pyannote.core 0.13

  • setup: switch to pyannote.parser 0.6.5

Version 0.13.2 (2017-01-30)

  • feat: add pyannote-metrics.py evaluation script

  • fix: fix BaseMetric.report() for metric without a ‘total’ component

  • fix: fix (Greedy)DiarizationErrorRate uem handling

  • fix: fix (Greedy)DiarizationErrorRate parallel processing

  • setup: switch to pyannote.core 0.12

  • setup: update munkres & matplotlib dependencies

Version 0.12.1 (2017-01-27)

  • feat: support for multiprocessing

  • feat: add report() method

  • feat: travis continuous integration (finally!)

  • improve: speed up detection metrics

  • feat: add unit tests for detection metrics

  • fix: fix python 3 support

  • setup: remove dependency to pyannote.algorithms

  • setup: switch to pyannote.core 0.11

Version 0.11 (2016-12-13)

  • feat: add pyannote.metrics.binary_classification module

Version 0.10.3 (2016-11-28)

  • fix: fix (greedy) diarization error rate

  • feat: add support for ‘collar’ to (greedy) diarization error rate

Version 0.10.2 (2016-11-10)

  • fix: fix default “xlim” in “plot_distributions”

  • setup: switch to pyannote.core 0.8 and pyannote.algorithms 0.6.6

Version 0.10.1 (2016-11-05)

  • feat: add “uem” support to diarization metrics

Version 0.9 (2016-09-23)

  • feat: add plotting functions for binary classification tasks

Version 0.8 (2016-08-25)

  • feat: detection accuracy

  • refactor: detection metrics

  • setup: update to pyannote.core 0.7.2

Version 0.7.1 (2016-06-24)

  • setup: update to pyannote.core 0.6.6

Version 0.7 (2016-04-04)

  • feat: greedy diarization error rate

Version 0.6.0 (2016-03-29)

  • feat: Python 3 support

  • feat: unit tests

  • wip: travis

Version 0.5.1 (2016-02-19)

  • refactor: diarization metrics

Version 0.4.1 (2014-11-20)

  • fix: identification error analysis matrix confusion

Version 0.4 (2014-10-31)

  • feat(error): identification regression analysis

  • feat: new pyannote_eval.py CLI

Version 0.3 (2014-10-01)

  • feat(error): segmentation error analysis

Version 0.2 (2014-08-05)

  • feat(detection): add precision and recall

  • fix(identification): fix precision and recall

Version 0.1 (2014-06-27)

  • feat(segmentation): add precision and recall

  • feat(identification): add support for NIST collar

  • feat(error): add module for detailed error analysis

Version 0.0.1 (2014-06-04)

  • first public version