/ Audio

Scalable audio processing framework and API written in Python

Scalable audio processing framework and API written in Python

TimeSide

audio processing framework for the web.

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,
  • Playback and interact on demand through a smart high-level HTML5 extensible player,
  • Index, tag and annotate audio archives with semantic metadata (see Telemeta <http://telemeta.org>__ which embed TimeSide).
  • Deploy and scale your own audio processing engine through any infrastructure

GitHub