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Sound Event Detection
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Sound Event Detection (SED) is the task of recognizing the sound events and their respective temporal start and end time in a recording. Sound events in real life do not always occur in isolation, but tend to considerably overlap with each other. Recognizing such overlapping sound events is referred as polyphonic SED.
Source: A report on sound event detection with different binaural features
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
FilterAugment: An Acoustic Environmental Data Augmentation Method
Peer Collaborative Learning for Polyphonic Sound Event Detection
Unsupervised Audio-Caption Aligning Learns Correspondences between Individual Sound Events and Textual Phrases
Sound Event Detection Transformer: An Event-based End-to-End Model for Sound Event Detection
SALSA: Spatial Cue-Augmented Log-Spectrogram Features for Polyphonic Sound Event Localization and Detection
The impact of non-target events in synthetic soundscapes for sound event detection
You Only Hear Once: A YOLO-like Algorithm for Audio Segmentation and Sound Event Detection
Uncertainty quantification for multiclass data description
Proposal-based Few-shot Sound Event Detection for Speech and Environmental Sounds with Perceivers
Crowdsourcing strong labels for sound event detection
What Makes Sound Event Localization and Detection Difficult? Insights from Error Analysis
Improving Polyphonic Sound Event Detection on Multichannel Recordings with the Sørensen-Dice Coefficient Loss and Transfer Learning
Sound Event Detection: A Tutorial
Weakly-Supervised Classification and Detection of Bird Sounds in the Wild.
Heavily Augmented Sound Event Detection utilizing Weak Predictions
Self-training with noisy student model and semi-supervised loss function for dcase 2021 challenge task 4
Robust and Interpretable Temporal Convolution Network for Event Detection in Lung Sound Recordings
DCASE 2021 Task 3: Spectrotemporally-aligned Features for Polyphonic Sound Event Localization and Detection
Affinity Mixup for Weakly Supervised Sound Event Detection
Do sound event representations generalize to other audio tasks? A case study in audio transfer learning
SoundDet: Polyphonic Moving Sound Event Detection and Localization from Raw Waveform
Improving weakly supervised sound event detection with self-supervised auxiliary tasks
Audiovisual transfer learning for audio tagging and sound event detection
Cross-Referencing Self-Training Network for Sound Event Detection in Audio Mixtures
USM-SED - A Dataset for Polyphonic Sound Event Detection in Urban Sound Monitoring Scenarios
Forward-Backward Convolutional Recurrent Neural Networks and Tag-Conditioned Convolutional Neural Networks for Weakly Labeled Semi-supervised Sound Event Detection
DESED-FL and URBAN-FL: Federated Learning Datasets for Sound Event Detection
Deep Convolutional and Recurrent Networks for Polyphonic Instrument Classification from Monophonic Raw Audio Waveforms
Sound Event Detection in Urban Audio With Single and Multi-Rate PCEN
Sound Event Detection with Binary Neural Networks on Tightly Power-Constrained IoT Devices
Soft-Median Choice: An Automatic Feature Smoothing Method for Sound Event Detection
ACCDOA: Activity-Coupled Cartesian Direction of Arrival Representation for Sound Event Localization and Detection
Improving Sound Event Detection Metrics: Insights from DCASE 2020
Power pooling: An adaptive pooling function for weakly labelled sound event detection
DCASENET: A joint pre-trained deep neural network for detecting and classifying acoustic scenes and events
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