Corpus ID: 51789184

CONVOLUTIONAL RECURRENT NEURAL NETWORKS FOR RARE SOUND EVENT DETECTION

@inproceedings{akir2017CONVOLUTIONALRN,
  title={CONVOLUTIONAL RECURRENT NEURAL NETWORKS FOR RARE SOUND EVENT DETECTION},
  author={Emre Çakir},
  year={2017}
}
Sound events possess certain temporal and spectral structure in their time-frequency representations. The spectral content for the samples of the same sound event class may exhibit small shifts due to intra-class acoustic variability. Convolutional layers can be used to learn high-level, shift invariant features from time-frequency representations of acoustic samples, while recurrent layers can be used to learn the longer term temporal context from the extracted high-level features. In this… Expand

Figures and Tables from this paper

Dilated-Gated Convolutional Neural Network with A New Loss Function on Sound Event Detection
Hierarchic Conv Nets Framework for Rare Sound Event Detection
Adaptive Multi-Scale Detection of Acoustic Events
  • Wenhao Ding, Liang He
  • Computer Science, Engineering
  • IEEE/ACM Transactions on Audio, Speech, and Language Processing
  • 2020
...
1
2
3
4
...

References

SHOWING 1-10 OF 20 REFERENCES
Convolutional Recurrent Neural Networks for Polyphonic Sound Event Detection
Polyphonic sound event detection using multi label deep neural networks
Convolutional recurrent neural networks for bird audio detection
Audio-based multimedia event detection using deep recurrent neural networks
Recurrent neural networks for polyphonic sound event detection in real life recordings
Acoustic event detection for multiple overlapping similar sources
  • D. Stowell, David Clayton
  • Computer Science
  • 2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)
  • 2015
DCASE 2017 Challenge setup: Tasks, datasets and baseline system
Reliable detection of audio events in highly noisy environments
...
1
2
...