# A simple model for detection of rare sound events

arXiv: https://arxiv.org/abs/1808.06676 · HTML: https://mlsanity.com/paper/1808.06676/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Aug 2018.

## Built on by (most cited first, 1 of 1)

- [Adaptive Few-Shot Learning Algorithm for Rare Sound Event Detection](https://mlsanity.com/paper/2205.11738/) (2022)

## Abstract (arXiv)

We propose a simple recurrent model for detecting rare sound events, when the time boundaries of events are available for training. Our model optimizes the combination of an utterance-level loss, which classifies whether an event occurs in an utterance, and a frame-level loss, which classifies whether each frame corresponds to the event when it does occur. The two losses make use of a shared vectorial representation the event, and are connected by an attention mechanism. We demonstrate our model on Task 2 of the DCASE 2017 challenge, and achieve competitive performance.