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20182024
most citedSound Event Detection: A Tutorial

265 citations · 269 across the 6 of their papers we have counts for

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11 papers · 1 filter

eess.AS2024

A decade of DCASE: Achievements, practices, evaluations and future challenges

Annamaria Mesaros, Romain Serizel, Toni Heittola +2

This paper introduces briefly the history and growth of the Detection and Classification of Acoustic Scenes and Events (DCASE) challenge, workshop, research area and research commu…

eess.AS2021

Crowdsourcing strong labels for sound event detection

Irene Martín-Morató, Manu Harju, Annamaria Mesaros

Strong labels are a necessity for evaluation of sound event detection methods, but often scarcely available due to the high resources required by the annotation task. We present a…

eess.AS2021265 cited

Sound Event Detection: A Tutorial

Annamaria Mesaros, Toni Heittola, Tuomas Virtanen +1

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 wh…

eess.AS2021

Low-complexity acoustic scene classification for multi-device audio: analysis of DCASE 2021 Challenge systems

Irene Martín-Morató, Toni Heittola, Annamaria Mesaros +1

This paper presents the details of Task 1A Acoustic Scene Classification in the DCASE 2021 Challenge. The task targeted development of low-complexity solutions with good generaliza…

eess.AS2021

Audio-visual scene classification: analysis of DCASE 2021 Challenge submissions

Shanshan Wang, Toni Heittola, Annamaria Mesaros +1

This paper presents the details of the Audio-Visual Scene Classification task in the DCASE 2021 Challenge (Task 1 Subtask B). The task is concerned with classification using audio…

eess.AS2021

What is the ground truth? Reliability of multi-annotator data for audio tagging

Irene Martin-Morato, Annamaria Mesaros

Crowdsourcing has become a common approach for annotating large amounts of data. It has the advantage of harnessing a large workforce to produce large amounts of data in a short ti…