Realtime Generation of Audible Textures Inspired by a Video Stream

No. 1: AAAI-19, IAAI-19, EAAI-20

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 33

Demonstration Track

We showcase a model to generate a soundscape from a camera stream in real time. The approach relies on a training video with an associated meaningful audio track; a granular synthesizer generates a novel sound by randomly sampling and mixing audio data from such video, favoring timestamps whose frame is similar to the current camera frame; the semantic similarity between frames is computed by a pretrained neural network. The demo is interactive: a user points a mobile phone to different objects and hears how the generated sound changes.

10.1609/aaai.v33i01.33019865