PILOT: Introducing Transformers for Probabilistic Sound Event Localization

Understand

Sound event localization aims at estimating the positions of sound sources in the environment with respect to an acoustic receiver (e.g.

• a microphone array).
• Recent advances in this domain most prominently focused on utilizing deep recurrent neural networks.
• Inspired by the success of transformer architectures as a suitable alternative to classical recurrent neural networks, this paper introduces a novel transformer-based sound event localization framework, where temporal dependencies in the received multi-channel audio signals are captured via self-attention mechanisms.