# Acoustic event detection for multiple overlapping similar sources

arXiv: https://arxiv.org/abs/1503.07150 · HTML: https://mlsanity.com/paper/1503.07150/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Mar 2015.

## Built on by (most cited first, 2 of 2)

- [Robust detection of overlapping bioacoustic sound events](https://mlsanity.com/paper/2503.02389/) (2025)
- [Advancing underwater acoustic target recognition via adaptive data pruning and smoothness-inducing regularization](https://mlsanity.com/paper/2304.11907/) (2023)

## Abstract (arXiv)

Many current paradigms for acoustic event detection (AED) are not adapted to the organic variability of natural sounds, and/or they assume a limit on the number of simultaneous sources: often only one source, or one source of each type, may be active. These aspects are highly undesirable for applications such as bird population monitoring. We introduce a simple method modelling the onsets, durations and offsets of acoustic events to avoid intrinsic limits on polyphony or on inter-event temporal patterns. We evaluate the method in a case study with over 3000 zebra finch calls. In comparison against a HMM-based method we find it more accurate at recovering acoustic events, and more robust for estimating calling rates.