Results 31 to 40 of about 313,816 (278)
Applied Sciences, 2021 In this paper, feature extraction methods are developed based on the non-negative matrix factorization (NMF) algorithm to be applied in weakly supervised sound event detection. Recently, the development of various features and systems have been attempted
Seokjin Lee +4 more
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MTF-CRNN: Multiscale Time-Frequency Convolutional Recurrent Neural Network for Sound Event Detection
IEEE Access, 2020 To reduce neural network parameter counts and improve sound event detection performance, we propose a multiscale time-frequency convolutional recurrent neural network (MTF-CRNN) for sound event detection.
Keming Zhang +4 more
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Convolutional Recurrent Neural Networks for Polyphonic Sound Event Detection [PDF]
, 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
core +2 more sources
Sound Event Detection Using Spatial Features and Convolutional Recurrent Neural Network [PDF]
, 2017 This paper proposes to use low-level spatial features extracted from multichannel audio for sound event detection. We extend the convolutional recurrent neural network to handle more than one type of these multichannel features by learning from each of ...
Adavanne, Sharath +2 more
core +2 more sources
A Comprehensive Review of Polyphonic Sound Event Detection
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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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
Large-scale weakly supervised audio classification using gated convolutional neural network [PDF]
, 2017 In this paper, we present a gated convolutional neural network and a temporal attention-based localization method for audio classification, which won the 1st place in the large-scale weakly supervised sound event detection task of Detection and ...
Kong, Qiuqiang +3 more
core +2 more sources
Seed: Sound Event Early Detection Via Evidential Uncertainty
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022 Sound Event Early Detection (SEED) is an essential task in recognizing the acoustic environments and soundscapes. However, most of the existing methods focus on the offline sound event detection, which suffers from the over-confidence issue of early-stage event detection and usually yield unreliable results.
Zhao, Xujiang +6 more
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Audio Captioning Using Sound Event Detection
, 2021 This technical report proposes an audio captioning system for DCASE 2021 Task 6 audio captioning challenge. Our proposed model is based on an encoder-decoder architecture with bi-directional Gated Recurrent Units (BiGRU) using pretrained audio features and sound event detection.
Eren, Ayşegül Özkaya, Sert, Mustafa
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