Dataset for polyphonic sound event detection tasks in urban soundscapes: The synthetic polyphonic ambient sound source (SPASS) dataset [PDF]
Data in Brief, 2023 This paper presents the Synthetic Polyphonic Ambient Sound Source (SPASS) dataset, a publicly available synthetic polyphonic audio dataset. SPASS was designed to train deep neural networks effectively for polyphonic sound event detection (PSED) in urban ...
Rhoddy Viveros-Muñoz +8 more
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Polyphonic Sound Event Detection Using Temporal-Frequency Attention and Feature Space Attention [PDF]
Sensors, 2022 The complexity of polyphonic sounds imposes numerous challenges on their classification. Especially in real life, polyphonic sound events have discontinuity and unstable time-frequency variations.
Ye Jin +4 more
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Metrics for Polyphonic Sound Event Detection [PDF]
Applied Sciences, 2016 This paper presents and discusses various metrics proposed for evaluation of polyphonic sound event detection systems used in realistic situations where there are typically multiple sound sources active simultaneously.
Annamaria Mesaros +2 more
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A Comprehensive Review of Polyphonic Sound Event Detection [PDF]
IEEE Access, 2020 One of the most amazing functions of the human auditory system is the ability to detect all kinds of sound events in the environment. With the technologies and hardware advances, polyphonic Sound Event Detection (SED) can be developed to mimic the ...
T. K. Chan, Cheng Siong Chin
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Polyphonic Sound Event Detection by using Capsule Neural Networks [PDF]
IEEE Journal of Selected Topics in Signal Processing, 2019 Artificial sound event detection (SED) has the aim to mimic the human ability to perceive and understand what is happening in the surroundings. Nowadays, Deep Learning offers valuable techniques for this goal such as Convolutional Neural Networks (CNNs).
Gabrielli, Leonardo +3 more
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Convolutional Recurrent Neural Networks for Polyphonic Sound Event Detection [PDF]
IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2017 Sound events often occur in unstructured environments where they exhibit wide variations in their frequency content and temporal structure. Convolutional neural networks (CNN) are able to extract higher level features that are invariant to local spectral
Heittola, Toni +4 more
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Analysis and interpretation of joint source separation and sound event detection in domestic environments. [PDF]
PLoS ONEIn recent years, the relation between Sound Event Detection (SED) and Source Separation (SSep) has received a growing interest, in particular, with the aim to enhance the performance of SED by leveraging the synergies between both tasks.
Diego de Benito-Gorrón +2 more
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Peer Collaborative Learning for Polyphonic Sound Event Detection
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022 This paper describes that semi-supervised learning called peer collaborative learning (PCL) can be applied to the polyphonic sound event detection (PSED) task, which is one of the tasks in the Detection and Classification of Acoustic Scenes and Events (DCASE) challenge.
Helen Bear +2 more
openaire +2 more sources
A System for the Detection of Polyphonic Sound on a University Campus Based on CapsNet-RNN
IEEE Access, 2021 In recent decades, surveillance and home security systems based on video analysis have been proposed for the automatic detection of abnormal situations.
Liyan Luo +6 more
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Improved capsule routing for weakly labeled sound event detection
EURASIP Journal on Audio, Speech, and Music Processing, 2022 Polyphonic sound event detection aims to detect the types of sound events that occur in given audio clips, and their onset and offset times, in which multiple sound events may occur simultaneously. Deep learning–based methods such as convolutional neural
Haitao Li, Shuguo Yang, Wenwu Wang
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