Interoperability

Easily agglomerate annotations from multiple sources into a corpus that you can query to gain insight and export into various formats.

Build complete HTML pages which can be read offline in any browser, or deployed on a webserver for public sharing.

AVAA Toolkit can be seamlessly integrated in existing toolchains thanks to its advanced command line.

Powered by battle-tested technologies like FFMPEG to process media files, and D3 for drawing charts.

AVAA also makes it easy to harness Python's AI ecosystem and R computing packages via simple interfaces.

Charts

Generate slick visualisations from data, refreshed instantly as the corpus gets updated.

Views

Display annotations with their associated media in interactive and meaningful ways.

and many more...

Processing

Modify a media file by applying audio filters on specific segments or video effects.

Automated transcription from audio to annotations, associated with their speaker tier.

Detect objects or faces in video, and generate corresponding annotations.

Transform media into other types, export annotations to many common formats.

Remove sections and export as a sub-corpus compatible with known annotators software.

Build advanced pipelines combining different features into an automated workflow.

Scriptable

AVAA Toolkit can be extended with JavaScript to perform specific tasks. The core engine allows scripting of several components via a powerful but simple API, making it a breeze to add custom functionalities and benefit from the editor's dynamic graphical user interface.
Actually, most of the things AVAA does are scripted! You can find and play with the code in the "scripts" folder, it's plain JS files. The full developer documentation will come soon but you can begin with the scripting guide