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open web audio processing framework

Project description

TimeSide is a set of python components enabling low and high level audio analysis, imaging, transcoding and streaming. Its high-level API is designed to enable complex processing on large datasets of audio and video assets of any format. Its simple plug-in architecture can be adapted to various use cases.

TimeSide also includes a smart interactive HTML5 player which provides various streaming playback functions, formats selectors, fancy audio visualizations, segmentation and semantic labelling synchronized with audio events. It is embeddable in any web application.

Build status

  • Branch master : travis_master coveralls_master
  • Branch dev : travis_dev coveralls_dev


  • Do asynchronous and fast audio processing with Python,
  • Decode audio frames from any audio or video media format into numpy arrays,
  • Analyze audio content with some state-of-the-art audio feature extraction libraries like Aubio, Yaafe and VAMP as well as some pure python processors
  • Visualize sounds with various fancy waveforms, spectrograms and other cool graphers,
  • Transcode audio data in various media formats and stream them through web apps,
  • Organize, serialize and save feature analysis data through various portable formats,
  • Playback and interact on demand through a smart high-level HTML5 extensible player,
  • Index, tag and annotate audio archives with semantic metadata (see Telemeta which embed TimeSide).


The streaming architecture of TimeSide relies on 2 main parts: a processing engine including various plugin processors written in pure Python and a user interface providing some web based visualization and playback tools in pure HTML5.;a=blob_plain;f=doc/slides/img/timeside_schema.svg;hb=refs/heads/dev



  • FileDecoder [gst_dec]
  • ArrayDecoder [array_dec]
  • LiveDecoder [gst_live_dec]


  • AubioTemporal [aubio_temporal]
  • AubioPitch [aubio_pitch]
  • AubioMfcc [aubio_mfcc]
  • AubioMelEnergy [aubio_melenergy]
  • AubioSpecdesc [aubio_specdesc]
  • Yaafe [yaafe]
  • Spectrogram [spectrogram_analyzer]
  • Waveform [waveform_analyzer]
  • VampSimpleHost [vamp_simple_host]
  • IRITSpeechEntropy [irit_speech_entropy]
  • IRITSpeech4Hz [irit_speech_4hz]
  • OnsetDetectionFunction [odf]
  • LimsiSad [limsi_sad]


  • Level [level]
  • MeanDCShift [mean_dc_shift]


  • Waveform [waveform_simple]
  • WaveformCentroid [waveform_centroid]
  • WaveformTransparent [waveform_transparent]
  • WaveformContourBlack [waveform_contour_black]
  • WaveformContourWhite [waveform_contour_white]
  • SpectrogramLog [spectrogram_log]
  • SpectrogramLinear [spectrogram_lin]
  • Display.aubio_pitch.pitch [grapher_aubio_pitch]
  • Display.odf [grapher_odf]
  • Display.waveform_analyzer [grapher_waveform]
  • Display.irit_speech_4hz.segments [grapher_irit_speech_4hz_segments]


  • VorbisEncoder [gst_vorbis_enc]
  • WavEncoder [gst_wav_enc]
  • Mp3Encoder [gst_mp3_enc]
  • FlacEncoder [gst_flac_enc]
  • AacEncoder [gst_aac_enc]
  • WebMEncoder [gst_webm_enc]
  • OpusEncoder [gst_opus_enc]
  • AudioSink [gst_audio_sink_enc]



  • Bugfix release
  • Fix analyzer instanciation as parent for some graphers


  • All processor folders (decoder, analyzer, grapher, encoder) are now real plugin repositories : you can just drop processors in it and play!
  • TimeSide can be installed without Aubio, Yaafe nor Vamp : it should be easier to install on old distributions for which those librairies are difficult or impossible to compile
  • Encoder : add an Opus encoder
  • Experimental : add a django web server with a REST API (see “Web server”)
  • AubioPitch: prevent NaN in result by converting them to zero
  • Yaafe analyzer: simplify adaptation of process frames from TimeSide to Yaafe
  • LimsiSad: add a default value for parameter sad_model
  • Fix various NaN and Inf and PEP8 issues also many PyFlake warnings
  • Full Travis integration with tests and test coverage through
  • Thanks to all contributors!
  • WARNING: some of the processor paths used in your app could have moved between 0.5.4 and 0.5.5. Check them with timeside.core.processors(). Note that it is now advised to use the timeside.core.get_processor() method to instantiate the processors with their respective id as argument.
  • UPGRADING from the sources: please remove all .pyc files from your repository.


  • Encoder : transcoded streams where broken. Now fixed with some smart thread controls.
  • Analyzer : update VAMP plugin example in sandbox
  • Analyzer : new experimental plugin : Limsi Speech Activity Detection Systems (limsi_sad)
  • Decoder : process any media in streaming mode giving its URL
  • Install : fix some setup requirements


  • Make Analyzer rendering more generic and easy to implement
  • Analyzer : implement rendering capability for event and segment + add some more analyzer graphers
  • Analyzer : refactoring the results rendering method. + Capability to use matplotlib in environnement with no display
  • Decoder : Add a Live decoder to get data from the soundcard
  • Decoder : add support for 96kHz sampling rate
  • Encoder: live AudioSink encoder, encoder that plays the audio stream through the soundcard
  • Grapher : add a generic Class to display Analyzers through their ‘render’ method. Add the new grapher file
  • Grapher : add a generic Class to display Analyzers through their ‘render’ method. For now, it only support FrameValueResult analyzer
  • Core : add a condition to catch signal only if a LiveDecoder source is used
  • Various bugfixes


  • Add a general launch script “timeside-launch” (see “Shell interface”)
  • Add some decorators to filter the inputs of processes (see analyzer.waveform for ex)
  • Add a “stack” option to the FileDecoder to accumulate audio data allowing multipass processes
  • Add beat confidence to aubio_temporal
  • Add AAC encoder (gstreamer voaacenc plugin needed)
  • Add UUIDs to the file URI and to all processors
  • Add a Debian repository with all dependencies for i386 and amd64 architectures
  • Fix buggy WebM encoder
  • Fix buggy MP3 muxing
  • Fix various minor bugs


  • Add parent processor list to Processor
  • Simplify and optimize the grapher system
  • Add Grapher abstract generic class
  • Add a UUID property to Processor
  • Add a SpectrogramLinear grapher
  • Add WaveformTransparent grapher
  • Fix some assignment issues regarding immutable type in for Analyzer Result
  • Simplify analyzer results implementation by introducing a Factory and multiple classes and subclasses to handle the 8 different kinds of results
  • Add doctests and improve the unit tests
  • Add a OnsetDetectionFunction analyzer
  • Update documentation
  • Various cleanups
  • Various bugfixes


  • Deep refactoring of the analyzer API to handle various new usecases, specifically audio feature extraction
  • Add serializable global result container (NEW dependency to h5py, json, yaml)
  • Add new audio feature extraction analyzers thanks to the Aubio library providing beat & BPM detection, pitch dectection and other cool stuff (NEW dependency on aubio)
  • Add new audio feature extraction analyzers thanks to the Yaafe library (NEW dependency on yaafe)
  • Add new IRIT speech detection analyzers (NEW dependency on scipy)
  • EXPERIMENTAL : add new audio feature extraction thanks to the VAMP plugin library (NEW dependency on some vamp toold)
  • Add new documentation :
  • New Debian repository for instant install
  • Various bugfixes
  • Comptatible with Python >=2.7
  • WARNING : no longer compatible with Telemeta 1.4.5

Dive in

To list all available plugins:

>>> import timeside
>>> timeside.core.list_processors()

Define some processors:

>>> from timeside.core import get_processor
>>> decoder  =  get_processor('gst_dec')('sweep.wav')
>>> grapher  =  get_processor('waveform_simple')
>>> analyzer =  get_processor('level')
>>> encoder  =  get_processor('gst_vorbis_enc')('sweep.ogg')

Then run the magic pipeline:

>>> (decoder | grapher | analyzer | encoder).run()

Render the grapher results:

>>> grapher.render(output='waveform.png')

Show the analyzer results:

>>> print 'Level:', analyzer.results

The encoded OGG file should also be there…

Note you can also instanciate each processor with its own class:

>>> decoder  =  timeside.decoder.file.FileDecoder('sweep.wav')
>>> grapher  =  timeside.grapher.waveform_simple.Waveform()
>>> analyzer =  timeside.analyzer.level.Level()
>>> encoder  =  timeside.encoder.ogg.VorbisEncoder('sweep.ogg')

For more extensive examples, please see the full documentation.


The TimeSide engine is intended to work on all Linux and Unix like platforms.

It depends on several other python modules and compiled librairies like GStreamer.

Debian, Ubuntu

For Debian based distributions, we provide a safe repository which provides all additional dependencies that are not included in Debian yet:

$ echo "deb stable main" | sudo tee -a /etc/apt/sources.list
$ sudo apt-get update
$ sudo apt-get install python-timeside

This method is known to be compatible with Debian 7 Wheezy with backports and Ubuntu 14.04 LTS. It will install additional binary packages from several audio feature extraction librairies like Aubio and Yaafe for which TimeSide has some nice processors.

Note you can also use pip if you already have already satisfied all the dependencies:

$ sudo pip install timeside

Other Linux distributions

On other Linux platforms, you need to install all dependencies listed in the paragraph “Dependencies” (find all equivalent package names for your distribution).

Then, use pip:

$ sudo pip install timeside


The installation on OSX platforms is pretty hard at the moment because all dependencies are not in brew. But, it will be fully documented in the next release 0.5.6.



python (>=2.7) python-setuptools python-numpy python-scipy python-h5py python-matplotlib pillow
python-simplejson python-yaml python-mutagen libhdf5-serial-dev python-gst0.10
gstreamer0.10-gnonlin gstreamer0.10-plugins-good gstreamer0.10-plugins-bad gstreamer0.10-plugins-ugly


aubio (>=0.4.1) yaafe python-aubio python-yaafe vamp-examples
django (>=1.4) django-south djangorestframework django-extensions

User Interfaces


Of course, TimeSide can be used in any python environment. But, a shell script is also provided to enable preset based and recursive processing through your command line interface:

$ timeside-launch -h
Usage: scripts/timeside-launch [options] -c file.conf file1.wav [file2.wav ...]
 help: scripts/timeside-launch -h

 -h, --help            show this help message and exit
 -v, --verbose         be verbose
 -q, --quiet           be quiet
 -C <config_file>, --conf=<config_file>
                       configuration file
 -s <samplerate>, --samplerate=<samplerate>
                       samplerate at which to run the pipeline
 -c <channels>, --channels=<channels>
                       number of channels to run the pipeline with
 -b <blocksize>, --blocksize=<blocksize>
                       blocksize at which to run the pipeline
 -a <analyzers>, --analyzers=<analyzers>
                       analyzers in the pipeline
 -g <graphers>, --graphers=<graphers>
                       graphers in the pipeline
 -e <encoders>, --encoders=<encoders>
                       encoders in the pipeline
 -R <formats>, --results-formats=<formats>
                       list of results output formats for the analyzers
 -I <formats>, --images-formats=<formats>
                       list of graph output formats for the analyzers results
 -o <outputdir>, --ouput-directory=<outputdir>
                       output directory

Web player

TimeSide comes with a smart and pure HTML5 audio player.

  • embed it in any audio web application
  • stream, playback and download various audio formats on the fly
  • synchronize sound with text, bitmap and vectorial events
  • seek through various semantic, analytic and time synced data
  • fully skinnable with CSS style
Examples of the player embeded in the Telemeta open web audio CMS:
Development documentation:
TODO list:
  • zoom
  • layers

Web server

An EXPERIMENTAL web server based on Django has been added to the package from version 0.5.5. The goal is to provide a full REST API to TimeSide to enable new kinds of audio processing web services.

A sandbox is provided in timeside/server/sandbox and you can initialize it and test it like this:

$ cd timeside/server/sandbox
$ ./ syncdb
$ ./ migrate
$ ./ runserver

and browse http://localhost:8000/api/

At the moment, this server is NOT connected to the player using TimeSide alone. Please use Telemeta.


For versions >=0.5 on Debian 7 Wheezy:

$ echo "deb stable main" | sudo tee -a /etc/apt/sources.list
$ echo "deb-src stable main" | sudo tee -a /etc/apt/sources.list
$ sudo apt-get update
$ sudo apt-get install git
$ sudo apt-get build-dep python-timeside

$ git clone
$ cd TimeSide
$ git checkout dev
$ sudo pip install -e .
$ python tests/run_all_tests

Sponsors and Partners

  • Parisson
  • CNRS (National Center of Science Research, France)
  • Huma-Num (big data equipment for digital humanities, ex TGE Adonis)
  • CREM (french National Center of Ethomusicology Research, France)
  • Université Pierre et Marie Curie (UPMC Paris, France)
  • ANR (CONTINT 2012 project : DIADEMS)
  • MNHN : Museum National d’Histoire Naturelle (Paris, France)


  • Copyright (c) 2006, 2014 Parisson SARL
  • Copyright (c) 2006, 2014 Guillaume Pellerin
  • Copyright (c) 2010, 2014 Paul Brossier
  • Copyright (c) 2013, 2014 Thomas Fillon
  • Copyright (c) 2013, 2014 Maxime Lecoz
  • Copyright (c) 2013, 2014 David Doukhan
  • Copyright (c) 2006, 2010 Samalyse SARL


TimeSide is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 2 of the License, or (at your option) any later version.

TimeSide is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

See LICENSE for more details.

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Filename, size & hash SHA256 hash help File type Python version Upload date
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