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