Awards

Challenge

Introduction

DCASE 2020 Challenge will offer awards for open-source and innovative methods. These awards are meant to encourage open science and reproducibility, and therefore the Reproducible System Award is directly based on these criteria. In addition, through our Judges’ Award we want to encourage novel and innovative approaches.

Each task will offer two awards. These awards aim to encourage participants to openly publish their code, and to use novel and problem-specific approaches and are therefore not directly based on the evaluation set performance ranking. We also highly encourage student authorship.

Awards

Open source Award

Reproducible system award

Reproducible system award will be offered for the highest scoring method that is open-source and fully reproducible. For full reproducibility, the authors must provide all the information needed to run the system and achieve the reported performance. The choice of licence is left to the author, but should ideally be selected among the ones approved by the Open Source Initiative.

Award recipients
Scenes Task 1

Hu Hu, Chao-Han (Huck) Yang, Xianjun Xia, Xue Bai, Xin Tang, Yajian Wang, Shutong Niu, Li Chai, Juanjuan Li, Hongning Zhu, Feng Bao, Yuanjun Zhao, Sabato Marco Siniscalchi, Yannan Wang, Jun Du, and Chin-Hui Lee

Device-Robust Acoustic Scene Classification Based on Two-Stage Categorization and Data Augmentation 		PDF
Monitoring Task 2

Paul Primus

Reframing Unsupervised Machine Condition Monitoring as a Supervised Classification Task with Outlier-Exposed Classifiers 		PDF
Localization Task 3

Yin Cao, Turab Iqbal, Qiuqiang Kong, Zhong Yue, Wenwu Wang, and Mark D. Plumbley

Event-Independent Network for Polyphonic Sound Event Localization and Detection 		PDF
Domestic Task 4

Janek Ebbers and Reinhold Haeb-Umbach

Convolutional Recurrent Neural Networks For Weakly Labeled Semi-Supervised Sound Event Detection In Domestic Environments 		PDF
Urban Task 5

Augustin Arnault and Nicolas Riche

CRNNs for Urban Sound Tagging with Spatiotemporal Context 		PDF
Caption Task 6

Yusong Wu, Kun Chen, Ziyue Wang, Xuan Zhang, Fudong Nian, Shengchen Li, and Xi Shao

Audio Captioning Based on Transformer and Pre-Training for 2020 DCASE Audio Captioning Challenge 		PDF
Judges Award

Judges’ award

Judges’ award will be offered for the method considered by the judges to be the most interesting or innovative. Criteria considered for this award include but are not limited to: originality, complexity, student participation, open-source, etc. Single model approaches are strongly preferred over ensembles; occasionally, small ensembles of different models can be considered, if the approach is innovative.

Award recipients
Scenes Task 1

Khaled Koutini, Florian Henkel, Hamid Eghbal-zadeh and Gerhard Widmer

CP-JKU Submissions to DCASE’20: Low-Complexity Cross-Device Acoustic Scene Classification with RF-Regularized CNNs 		PDF
Monitoring Task 2

Tomoki Hayashi, Takenori Yoshimura and Yusuke Adachi

Conformer-based ID-Aware Autoencoder for Unsupervised Anomalous Sound Detection 		PDF
Localization Task 3

Andrés Pérez-López and Rafael Ibáñez-Usach

PAPAFIL: A Low Complexity Sound Event Localization and Detection Method with Parametric Particle Filtering and Gradient Boosting 		PDF
Domestic Task 4

Samuele Cornell, Giovanni Pepe, Emanuele Principi, Manuel Pariente, Michel Olvera, Leonardo Gabrielli, and Stefano Squartini

The UNIVPM-INRIA Systems For The DCASE 2020 Task 4 		PDF
Urban Task 5

Turab Iqbal, Yin Cao, Mark D. Plumbley and Wenwu Wang

Incorporating Auxiliary Data for Urban Sound Tagging 		PDF
Caption Task 6

Yuma Koizumi, Daiki Takeuchi, Yasunori Ohishi, Noboru Harada and Kunio Kashino

The NTT DCASE2020 Challenge Task 6 System: Automated Audio Captioning With Keywords and Sentence Length Estimation 		PDF