CochlScene: Acquisition of acoustic scene data using crowdsourcing

M. Eskenazi, G.-A. Levow, H. Meng, G. Parent, and D. Suendermann, “Crowdsourcing for speech processing: Applications to data collection, transcription and assessment,” John Wiley & Sons, 2013

2013

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D. Barchiesi, D. Giannoulis, D. Stowell, and M. D. Plumbley, “Acoustic scene classification: Classifying environments from the sounds they produce,” IEEE Signal Processing Magazine, vol. 32, no. 3, 2015

2015

Earlier work this paper cites.

A. Rakotomamonjy and G. Gasso, “Histogram of gradients of time-frequency representations for audio scene classification,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 23, no. 1, 2015

2015

Earlier work this paper cites.

A. Mesaros, T. Heittola, and T. Virtanen, “TUT database for acoustic scene classification and sound event detection,” in proceedings of European Signal Processing Conference (EUSIPCO), 2016

2016

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M. Buhrmester, T. Kwang, and S. D. Gosling, “Amazon’s Mechanical Turk: A new source of inexpensive, yet high-quality data?,” Perspectives on Psychological Science, vol. 6, no. 1, 2016

2016

Earlier work this paper cites.

Y. Han, J. Park, and K. Lee, “Convolutional neural networks with binaural representations and background subtraction for acoustic scene classification,” in proceedings of the Detection and Classification of Acoustic Scenes and Events Workshop (DCASE), 2017

2017

Cited alongside, same era.

A. Mesaros, T. Heittola, A. Diment, B. Elizalde, A. Shah, E. Vincent, B. Raj, and T. Virtanen, “DCASE 2017 challenge setup: tasks, datasets and baseline system,” in proceedings of the Detection and Classification of Acoustic Scenes and Events Workshop (DCASE), 2017

2017

Cited alongside, same era.

K. Choi, D. Joo, and J. Kim, “Kapre: On-GPU audio preprocessing layers for a quick implementation of deep neural network models with Keras,” in proceedings of Machine Learning for Music Discovery Workshop at International Conference on Machine Learning (ICML), 2017

Original

2017

Cited alongside, same era.

A. Mesaros, T. Heittola, and T. Virtanen, “A multi-device dataset for urban acoustic scene classification,” in proceedings of the Detection and Classification of Acoustic Scenes and Events Workshop (DCASE), 2018

T. Heittola, A. Mesaros, and T. Virtanen, “Acoustic scene classification in dcase 2020 challenge: generalization across devices and low complexity solution,”. in proceedings of the Detection and Classification of Acoustic Scenes and Events Workshop (DCASE), 2020

2020

Later among the works it cites.

S. Park, et al., “KLUE: Korean language understanding evaluation,” arXiv:2105.09680, 2021

Original

2021

Later among the works it cites.

E. Fonseca, X. Favory, J. Pons, F. Font, and X. Serra, “Fsd50k: an open dataset of human-labeled sound events,” IEEE/ACM Transactions on Audio, Speech, and Language Processing , 2021

2021

Later among the works it cites.

H. Lee and J. Park, “Instance-wise occlusion and depth orders in natural scenes,” in proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022

2022

Closest in time.