# Sound Event Detection: A Tutorial

arXiv: https://arxiv.org/abs/2107.05463 · HTML: https://mlsanity.com/paper/2107.05463/

## Key facts

- Cited by 51 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Jul 2021.

## Built on by (most cited first, 30 of 51)

- [WavCaps: A ChatGPT-Assisted Weakly-Labelled Audio Captioning Dataset for Audio-Language Multimodal Research](https://mlsanity.com/paper/2303.17395/) (2023)
- [HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection](https://mlsanity.com/paper/2202.00874/) (2022)
- [FunAudioLLM: Voice Understanding and Generation Foundation Models for Natural Interaction Between Humans and LLMs](https://mlsanity.com/paper/2407.04051/) (2024)
- [Sound-Guided Semantic Image Manipulation](https://mlsanity.com/paper/2112.00007/) (2021)
- [Sound-Guided Semantic Video Generation](https://mlsanity.com/paper/2204.09273/) (2022)
- [M^4I: Multi-modal Models Membership Inference](https://mlsanity.com/paper/2209.06997/) (2022)
- [PHNNs: Lightweight Neural Networks via Parameterized Hypercomplex Convolutions](https://mlsanity.com/paper/2110.04176/) (2021)
- [Automated Audio Captioning: An Overview of Recent Progress and New Challenges](https://mlsanity.com/paper/2205.05949/) (2022)
- [Multi-Scale Attention for Audio Question Answering](https://mlsanity.com/paper/2305.17993/) (2023)
- [When Audio and Text Disagree: Revealing Text Bias in Large Audio-Language Models](https://mlsanity.com/paper/2508.15407/) (2025)
- [Pushing the Frontier of Audiovisual Perception with Large-Scale Multimodal Correspondence Learning](https://mlsanity.com/paper/2512.19687/) (2025)
- [DPM-TSE: A Diffusion Probabilistic Model for Target Sound Extraction](https://mlsanity.com/paper/2310.04567/) (2023)
- [Simple Pooling Front-ends For Efficient Audio Classification](https://mlsanity.com/paper/2210.00943/) (2022)
- [Detect Any Sound: Open-Vocabulary Sound Event Detection with Multi-Modal Queries](https://mlsanity.com/paper/2507.16343/) (2025)
- [Recognizing Ornaments in Vocal Indian Art Music with Active Annotation](https://mlsanity.com/paper/2505.04419/) (2025)
- [Audiomer: A Convolutional Transformer For Keyword Spotting](https://mlsanity.com/paper/2109.10252/) (2021)
- [DiffSED: Sound Event Detection with Denoising Diffusion](https://mlsanity.com/paper/2308.07293/) (2023)
- [What Are They Doing? Joint Audio-Speech Co-Reasoning](https://mlsanity.com/paper/2409.14526/) (2024)
- [Language-based Audio Moment Retrieval](https://mlsanity.com/paper/2409.15672/) (2024)
- [ZeroSep: Separate Anything in Audio with Zero Training](https://mlsanity.com/paper/2505.23625/) (2025)
- [FlexSED: Towards Open-Vocabulary Sound Event Detection](https://mlsanity.com/paper/2509.18606/) (2025)
- [Segment-level Metric Learning for Few-shot Bioacoustic Event Detection](https://mlsanity.com/paper/2207.07773/) (2022)
- [Balanced Deep CCA for Bird Vocalization Detection](https://mlsanity.com/paper/2211.09376/) (2022)
- [Prototype based Masked Audio Model for Self-Supervised Learning of Sound Event Detection](https://mlsanity.com/paper/2409.17656/) (2024)
- [Via Score to Performance: Efficient Human-Controllable Long Song Generation with Bar-Level Symbolic Notation](https://mlsanity.com/paper/2508.01394/) (2025)
- [Dual Knowledge Distillation for Efficient Sound Event Detection](https://mlsanity.com/paper/2402.02781/) (2024)
- [Aggregation Strategies for Efficient Annotation of Bioacoustic Sound Events Using Active Learning](https://mlsanity.com/paper/2503.02422/) (2025)
- [Sound event localization and classification using WASN in Outdoor Environment](https://mlsanity.com/paper/2403.20130/) (2024)
- [Automated Bioacoustic Monitoring for South African Bird Species on Unlabeled Data](https://mlsanity.com/paper/2406.13579/) (2024)
- [LHGNN: Local-Higher Order Graph Neural Networks For Audio Classification and Tagging](https://mlsanity.com/paper/2501.03464/) (2025)

## Abstract (arXiv)

The goal of automatic sound event detection (SED) methods is to recognize what is happening in an audio signal and when it is happening. In practice, the goal is to recognize at what temporal instances different sounds are active within an audio signal. This paper gives a tutorial presentation of sound event detection, including its definition, signal processing and machine learning approaches, evaluation, and future perspectives.