TimeSide : scalable audio processing framework and server written in Python¶
TimeSide is a python framework enabling low and high level audio analysis, imaging, transcoding, streaming and labelling. Its high-level API is designed to enable complex processing on very large datasets of any audio or video assets with a plug-in architecture, a secure scalable backend and an extensible dynamic web frontend.
Use cases¶
Scaled audio computing (filtering, machine learning, etc)
Web audio visualization
Audio process prototyping
Realtime and on-demand transcoding and streaming over the web
Automatic segmentation and labelling synchronized with audio events
Goals¶
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,
Serialize feature analysis data through various portable formats,
Provide audio sources from plateform like YouTube or Deezer
Deliver analysis and transcode on provided or uploaded tracks over the web through a REST API
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).
Deploy and scale your own audio processing engine through any infrastructure
Funding and support¶
To fund the project and continue our fast development process, we need your explicit support. So if you use TimeSide in production or even in a development or experimental setup, please let us know by:
staring or forking the project on GitHub
tweeting something to @parisson_studio or @telemeta
drop us an email on <support@parisson.com> or <pow@ircam.fr>
Thanks for your help!