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Commit eb6ec291 authored by Pavel KORSHUNOV's avatar Pavel KORSHUNOV
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Correcting links in readme

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...@@ -25,7 +25,7 @@ diarization pipeline that relies on pyannote_ framework. ...@@ -25,7 +25,7 @@ diarization pipeline that relies on pyannote_ framework.
Essentially, this package is a set of helper scripts and a documentation Essentially, this package is a set of helper scripts and a documentation
on how to run and reproduce the diarization experiments using pyannote_ on how to run and reproduce the diarization experiments using pyannote_
diarization framework. This documentation let you setup the pyannote_ diarization framework. This documentation let you setup the pyannote_
environment to reproduce training and evaluating several paynnote_ based environment to reproduce training and evaluating several pyannote_ based
models for voice activity detection (VAD), speaker change detection (SPD), models for voice activity detection (VAD), speaker change detection (SPD),
and embeddings (EMB). Also, we provide several scripts for computing various and embeddings (EMB). Also, we provide several scripts for computing various
metrics for measuring the performance of the trained models. metrics for measuring the performance of the trained models.
...@@ -90,7 +90,7 @@ In our experiments, we have used the following databases: ...@@ -90,7 +90,7 @@ In our experiments, we have used the following databases:
(full database), CallHome_ (train subset), LibriSpeech_ (other-train subset), (full database), CallHome_ (train subset), LibriSpeech_ (other-train subset),
and AMI_ (train subset). This collection was used for training different and AMI_ (train subset). This collection was used for training different
models of diarization pipeline. models of diarization pipeline.
- LargeMeta_ - a larger collection of databases, including SmallMeta - LargeMeta - a larger collection of databases, including SmallMeta
plus REPERE_ (train subsets of phase 1 and 2), ESTER (train subsets of plus REPERE_ (train subsets of phase 1 and 2), ESTER (train subsets of
ESTER1_ and ESTER2_), and LibriSpeech_ (clean-train subset). This collection ESTER1_ and ESTER2_), and LibriSpeech_ (clean-train subset). This collection
was used for training different models of diarization pipeline. was used for training different models of diarization pipeline.
...@@ -104,7 +104,7 @@ In our experiments, we have used the following databases: ...@@ -104,7 +104,7 @@ In our experiments, we have used the following databases:
Internet telephony. The whole database was used to test all of the above Internet telephony. The whole database was used to test all of the above
pre-trained models and hyper-parameters. pre-trained models and hyper-parameters.
Almost all databases, have paynnote_ database package available, so that it is Almost all databases, have pyannote_ database package available, so that it is
easy to use these databases (once the data itself is downloaded, which should easy to use these databases (once the data itself is downloaded, which should
be done separately with each databases copyright holders). Here is the list be done separately with each databases copyright holders). Here is the list
of corresponding database packages that can be installed: of corresponding database packages that can be installed:
...@@ -275,7 +275,7 @@ development `mailing list`_. ...@@ -275,7 +275,7 @@ development `mailing list`_.
.. _Librispeech: http://www.openslr.org/12 .. _Librispeech: http://www.openslr.org/12
.. _AMI: http://groups.inf.ed.ac.uk/ami/download/ .. _AMI: http://groups.inf.ed.ac.uk/ami/download/
.. _REPERE: https://www.aclweb.org/anthology/L12-1410/ .. _REPERE: https://www.aclweb.org/anthology/L12-1410/
.. _ESTER: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0241/ .. _ESTER1: http://catalogue.elra.info/en-us/repository/browse/ELRA-S0241/
.. _ESTER2: http://catalog.elra.info/en-us/repository/browse/ELRA-S0338/ .. _ESTER2: http://catalog.elra.info/en-us/repository/browse/ELRA-S0338/
.. _DIHARD: https://coml.lscp.ens.fr/dihard/index.html .. _DIHARD: https://coml.lscp.ens.fr/dihard/index.html
.. _ODESSA: https://www.idiap.ch/dataset/odessa/ .. _ODESSA: https://www.idiap.ch/dataset/odessa/
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