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Related papers: Real-Time Sound Event Localization and Detection: …

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We aim to perform sound event localization and detection (SELD) using wearable equipment for a moving human, such as a pedestrian. Conventional SELD tasks have dealt only with microphone arrays located in static positions. However,…

Audio and Speech Processing · Electrical Eng. & Systems 2024-03-05 Masahiro Yasuda , Shoichiro Saito , Akira Nakayama , Noboru Harada

Sound event localization and detection (SELD) aims to determine the appearance of sound classes, together with their Direction of Arrival (DOA). However, current SELD systems can only predict the activities of specific classes, for example,…

Audio and Speech Processing · Electrical Eng. & Systems 2024-06-25 Jinzheng Zhao , Xinyuan Qian , Yong Xu , Haohe Liu , Yin Cao , Davide Berghi , Wenwu Wang

This report presents our systems submitted to the audio-only and audio-visual tracks of the DCASE2025 Task 3 Challenge: Stereo Sound Event Localization and Detection (SELD) in Regular Video Content. SELD is a complex task that combines…

Audio and Speech Processing · Electrical Eng. & Systems 2025-07-08 Davide Berghi , Philip J. B. Jackson

This report presents the dataset and the evaluation setup of the Sound Event Localization & Detection (SELD) task for the DCASE 2020 Challenge. The SELD task refers to the problem of trying to simultaneously classify a known set of sound…

Audio and Speech Processing · Electrical Eng. & Systems 2020-06-30 Archontis Politis , Sharath Adavanne , Tuomas Virtanen

Polyphonic sound event detection and localization (SELD) task is challenging because it is difficult to jointly optimize sound event detection (SED) and direction-of-arrival (DOA) estimation in the same network. We propose a general network…

Audio and Speech Processing · Electrical Eng. & Systems 2020-11-17 Thi Ngoc Tho Nguyen , Ngoc Khanh Nguyen , Huy Phan , Lam Pham , Kenneth Ooi , Douglas L. Jones , Woon-Seng Gan

Sound event localization and detection (SELD) systems estimate both the direction-of-arrival (DOA) and class of sound sources over time. In the DCASE 2022 SELD Challenge (Task 3), models are designed to operate in a 4-channel setting. While…

This technical report presents our submission to Task 3 of the DCASE 2025 Challenge: Stereo Sound Event Localization and Detection (SELD) in Regular Video Content. We address the audio-only task in this report and introduce several key…

Audio and Speech Processing · Electrical Eng. & Systems 2025-07-02 Jun-Wei Yeow , Ee-Leng Tan , Santi Peksi , Woon-Seng Gan

Joint sound event localization and detection (SELD) is an emerging audio signal processing task adding spatial dimensions to acoustic scene analysis and sound event detection. A popular approach to modeling SELD jointly is using…

Sound · Computer Science 2021-09-28 Parthasaarathy Sudarsanam , Archontis Politis , Konstantinos Drossos

Sound event localization and detection (SELD) combines two subtasks: sound event detection (SED) and direction of arrival (DOA) estimation. SELD is usually tackled as an audio-only problem, but visual information has been recently included.…

Audio and Speech Processing · Electrical Eng. & Systems 2023-12-15 Davide Berghi , Peipei Wu , Jinzheng Zhao , Wenwu Wang , Philip J. B. Jackson

In this paper, we propose a convolutional recurrent neural network for joint sound event localization and detection (SELD) of multiple overlapping sound events in three-dimensional (3D) space. The proposed network takes a sequence of…

Sound · Computer Science 2018-12-18 Sharath Adavanne , Archontis Politis , Joonas Nikunen , Tuomas Virtanen

For learning-based sound event localization and detection (SELD) methods, different acoustic environments in the training and test sets may result in large performance differences in the validation and evaluation stages. Different…

Audio and Speech Processing · Electrical Eng. & Systems 2023-08-21 Jinbo Hu , Yin Cao , Ming Wu , Feiran Yang , Ziying Yu , Wenwu Wang , Mark D. Plumbley , Jun Yang

Sound event detection (SED) is a hot topic in consumer and smart city applications. Existing approaches based on Deep Neural Networks are very effective, but highly demanding in terms of memory, power, and throughput when targeting…

Machine Learning · Computer Science 2021-01-13 Gianmarco Cerutti , Renzo Andri , Lukas Cavigelli , Michele Magno , Elisabetta Farella , Luca Benini

We propose a benchmark of state-of-the-art sound event detection systems (SED). We designed synthetic evaluation sets to focus on specific sound event detection challenges. We analyze the performance of the submissions to DCASE 2021 task 4…

Wearable audio devices with active noise control (ANC) enhance listening comfort but often at the expense of situational awareness. However, this auditory isolation may mask crucial environmental cues, posing significant safety risks. To…

Audio and Speech Processing · Electrical Eng. & Systems 2025-10-09 Jun-Wei Yeow , Ee-Leng Tan , Santi Peksi , Zhen-Ting Ong , Woon-Seng Gan

Accurate recognition of Emergency Vehicle (EV) sirens is critical for the integration of intelligent transportation systems, smart city monitoring systems, and autonomous driving technologies. Modern automatic solutions are limited by the…

Sound · Computer Science 2025-07-01 Stefano Giacomelli , Marco Giordano , Claudia Rinaldi , Fabio Graziosi

In this paper, we describe our method for DCASE2019 task3: Sound Event Localization and Detection (SELD). We use four CRNN SELDnet-like single output models which run in a consecutive manner to recover all possible information of occurring…

Audio and Speech Processing · Electrical Eng. & Systems 2019-10-31 Sławomir Kapka , Mateusz Lewandowski

As deeper and more complex models are developed for the task of sound event localization and detection (SELD), the demand for annotated spatial audio data continues to increase. Annotating field recordings with 360$^{\circ}$ video takes…

Audio and Speech Processing · Electrical Eng. & Systems 2023-09-08 Christopher Ick , Brian McFee

Sound event localization and detection (SELD) is an important task in machine listening. Major advancements rely on simulated data with sound events in specific rooms and strong spatio-temporal labels. SELD data is simulated by convolving…

Audio and Speech Processing · Electrical Eng. & Systems 2024-01-24 Iran R. Roman , Christopher Ick , Sivan Ding , Adrian S. Roman , Brian McFee , Juan P. Bello

In recent years, deep learning systems have shown a concerning trend toward increased complexity and higher energy consumption. As researchers in this domain and organizers of one of the Detection and Classification of Acoustic Scenes and…

Audio and Speech Processing · Electrical Eng. & Systems 2024-01-18 Francesca Ronchini , Romain Serizel

This paper presents the objective, dataset, baseline, and metrics of Task 3 of the DCASE2025 Challenge on sound event localization and detection (SELD). In previous editions, the challenge used four-channel audio formats of first-order…