Attention and Localization based on a Deep Convolutional Recurrent Model for Weakly Supervised Audio Tagging

Understand

Audio tagging aims to perform multi-label classification on audio chunks and it is a newly proposed task in the Detection and Classification of Acoustic Scenes and Events 2016 (DCASE 2016) challenge.

• This task encourages research efforts to better analyze and understand the content of the huge amounts of audio data on the web.
• The difficulty in audio tagging is that it only has a chunk-level label without a frame-level label.
• This paper presents a weakly supervised method to not only predict the tags but also indicate the temporal locations of the occurred acoustic events.