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Sound Event Detection: A Tutorial

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arxiv 2107.05463 v1 pith:5TWSNZUW submitted 2021-07-12 eess.AS

Annamaria Mesaros , Toni Heittola , Tuomas Virtanen , Mark D. Plumbley This is my paper
classification eess.AS
keywords detectioneventsignalsoundaudiogoalhappeningrecognize
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 1 Pith paper

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  1. Exploring Feature Extraction Technique Parameters for Acoustic Gunshot Classification

    cs.SD 2026-06 unverdicted novelty 4.0 of 10

    Systematic benchmark of feature extraction techniques and parameters for gunshot audio classification shows up to 20% top-1 accuracy gain from technique choice and 4.7% from parameter tuning on a 23k-recording dataset.

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