https://github.com/bbc/diarize-jruby
A simple toolkit for speaker segmentation and identification
https://github.com/bbc/diarize-jruby
Last synced: 9 months ago
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A simple toolkit for speaker segmentation and identification
- Host: GitHub
- URL: https://github.com/bbc/diarize-jruby
- Owner: bbc
- License: other
- Created: 2013-06-14T16:02:48.000Z (over 12 years ago)
- Default Branch: master
- Last Pushed: 2013-06-15T16:32:37.000Z (over 12 years ago)
- Last Synced: 2025-03-22T06:51:15.814Z (10 months ago)
- Language: Ruby
- Size: 3.06 MB
- Stars: 30
- Watchers: 28
- Forks: 8
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: COPYING
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README
diarize-jruby
=============
This library provides an easy-to-use toolkit for speaker
segmentation (diarization) and identification from audio.
This library is being used within the BBC R&D World Service
archive prototype.
See http://worldservice.prototyping.bbc.co.uk/programmes/X0403940 for
an example.
Speaker diarization
-------------------
This library gives acccess to the algorithm developed by the LIUM
for the ESTER 2 evaluation campaign and described in [Meigner2010].
It wraps a binary JAR file compiled from
http://lium3.univ-lemans.fr/diarization/doku.php/welcome.
Speaker identification
----------------------
This library also implements an algorithm for speaker identification
based on the comparison of normalised speaker models, which can be
accessed through the Speaker#match method.
This algorithm builds on top of the LIUM toolkit and uses the following
techniques:
* "M-Norm" normalisation of speaker models [Ben2003]
* The symmetric Kullback-Leibler divergence approximation described in [Do2003]
* The detection score specified in [Ben2005]
It also includes support for speaker supervectors [Campbell2006], which
can be used in combination with our ruby-lsh library for fast speaker
identification.
Example use
-----------
This gem has been tested with jruby 1.7.0 onwards.
$ jruby -S gem install diarize-jruby
$ jruby -S irb
> require 'diarize'
> audio = Diarize::Audio.new URI('http://example.com/file.wav')
> audio.analyze!
> audio.segments
> audio.speakers
> audio.to_rdf
> speakers = audio.speakers
> speakers.first.gender
> speakers.first.model.mean_log_likelihood
> speakers.first.model.components.size
> audio.segments_by_speaker(speakers.first)[0].play
> audio.segments_by_speaker(speakers.first)[1].play
> ...
> speakers |= other_speakers
> Diarize::Speaker.match(speakers)
Running tests
-------------
$ jruby -S rake
References
----------
[Meigner2010] S. Meignier and T. Merlin, "LIUM SpkDiarization:
An Open Source Toolkit For Diarization" in Proc. CMU SPUD Workshop,
March 2010, Dallas (Texas, USA)
[Ben2003] M. Ben and F. Bimbot, "D-MAP: A Distance-Normalized Map
Estimation of SPeaker Models for Automatic Speaker Verification",
Proceedings of ICASSP, 2003
[Do2003] M. N. Do, "Fast Approximation of Kullback-Leibler Distance
for Dependence Trees and Hidden Markov Models",
IEEE Signal Processing Letters, April 2003
[Ben2005] M. Ben and G. Gravier and F. Bimbot. "A model space
framework for efficient speaker detection",
Proceedings of INTERSPEECH, 2005
[Campbell2006] W. M. Campbell, D. E. Sturim and D. A. Reynolds,
"Support vector machines using GMM supervectors for speaker verification",
IEEE Signal Processing Letters, 2006, 13, 308-311
Licensing terms and authorship
------------------------------
See 'COPYING' and 'AUTHORS' files.
All code here, except where otherwise indicated, is licensed under
the GNU Affero General Public License version 3. This license includes
many restrictions. If this causes a problem, please contact us.
See "AUTHORS" for contact details.
This library includes a binary JAR file from the LIUM project, which code
is licensed under the GNU General Public License version 2. See
http://lium3.univ-lemans.fr/diarization/doku.php/licence for more
information.