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ORCID5th DCASE 2020, Tokyo, Japan
- Nobutaka Ono, Noboru Harada, Yohei Kawaguchi, Annamaria Mesaros, Keisuke Imoto, Yuma Koizumi, Tatsuya Komatsu:
Proceedings of 5th the Workshop on Detection and Classification of Acoustic Scenes and Events 2020 (DCASE 2020), Tokyo, Japan (full virtual), November 2-4, 2020. 2020, ISBN 978-4-600-00566-5 - Ohad Barak, Nizar Sallem, Marc Fischer:
Microphone Array Optimization for Autonomous-Vehicle Audio Localization Based on the Radon Transform. 1-5 - Emre Çakir, Konstantinos Drossos, Tuomas Virtanen:
Multi-Task Regularization Based on Infrequent Classes for Audio Captioning. 6-10 - Yin Cao, Turab Iqbal, Qiuqiang Kong, Yue Zhong, Wenwu Wang, Mark D. Plumbley:
Event-Independent Network for Polyphonic Sound Event Localization and Detection. 11-15 - Mark Cartwright, Jason Cramer, Ana Elisa Méndez Méndez, Yu Wang, Ho-Hsiang Wu, Vincent Lostanlen, Magdalena Fuentes, Graham Dove, Charlie Mydlarz, Justin Salamon, Oded Nov, Juan Pablo Bello:
SONYC-UST-V2: An Urban Sound Tagging Dataset with Spatiotemporal Context. 16-20 - Kun Chen, Yusong Wu, Ziyue Wang, Xuan Zhang, Fudong Nian, Shengchen Li, Xi Shao:
Audio Captioning Based on Transformer and Pre-Trained CNN. 21-25 - Samuele Cornell, Michel Olvera, Manuel Pariente, Giovanni Pepe, Emanuele Principi, Leonardo Gabrielli, Stefano Squartini:
Domain-Adversarial Training and Trainable Parallel Front-End for the DCASE 2020 Task 4 Sound Event Detection Challenge. 26-30 - Samuele Cornell, Michel Olvera, Manuel Pariente, Giovanni Pepe, Emanuele Principi, Leonardo Gabrielli, Stefano Squartini:
Task-Aware Separation for the DCASE 2020 Task 4 Sound Event Detection and Separation Challenge. 31-35 - Diego de Benito-Gorrón, Daniel Ramos, Doroteo T. Toledano:
A Multi-Resolution Approach to Sound Event Detection in DCASE 2020 Task4. 36-40 - Janek Ebbers, Reinhold Haeb-Umbach:
Forward-Backward Convolutional Recurrent Neural Networks and Tag-Conditioned Convolutional Neural Networks for Weakly Labeled Semi-Supervised Sound Event Detection. 41-45 - Ritwik Giri, Srikanth V. Tenneti, Fangzhou Cheng, Karim Helwani, Umut Isik, Arvindh Krishnaswamy:
Self-Supervised Classification for Detecting Anomalous Sounds. 46-50 - Ritwik Giri, Fangzhou Cheng, Karim Helwani, Srikanth V. Tenneti, Umut Isik, Arvindh Krishnaswamy:
Group Masked Autoencoder Based Density Estimator for Audio Anomaly Detection. 51-55 - Toni Heittola, Annamaria Mesaros, Tuomas Virtanen:
Acoustic Scene Classification in DCASE 2020 Challenge: Generalization Across Devices and Low Complexity Solutions. 56-60 - Yuxin Huang, Liwei Lin, Shuo Ma, Xiangdong Wang, Hong Liu, Yueliang Qian, Min Liu, Kazushige Ouchi:
Guided Multi-Branch Learning Systems for Sound Event Detection with Sound Separation. 61-65 - Tadanobu Inoue, Phongtharin Vinayavekhin, Shu Morikuni, Shiqiang Wang, Tuan Hoang Trong, David Wood, Michiaki Tatsubori, Ryuki Tachibana:
Detection of Anomalous Sounds for Machine Condition Monitoring using Classification Confidence. 66-70 - Slawomir Kapka:
ID-Conditioned Auto-Encoder for Unsupervised Anomaly Detection. 71-75 - Ju-ho Kim, Jee-Weon Jung, Hye-Jin Shim, Ha-Jin Yu:
Audio Tag Representation Guided Dual Attention Network for Acoustic Scene Classification. 76-80 - Yuma Koizumi, Yohei Kawaguchi, Keisuke Imoto, Toshiki Nakamura, Yuki Nikaido, Ryo Tanabe, Harsh Purohit, Kaori Suefusa, Takashi Endo, Masahiro Yasuda, Noboru Harada:
Description and Discussion on DCASE2020 Challenge Task2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring. 81-85 - Khaled Koutini, Florian Henkel, Hamid Eghbal-Zadeh, Gerhard Widmer:
Low-Complexity Models for Acoustic Scene Classification Based on Receptive Field Regularization and Frequency Damping. 86-90 - Alisa Liu, Prem Seetharaman, Bryan Pardo:
Model Selection for Deep Audio Source Separation via Clustering Analysis. 91-95 - Jose A. Lopez, Hong Lu, Paulo Lopez-Meyer, Lama Nachman, Georg Stemmer, Jonathan Huang:
A Speaker Recognition Approach to Anomaly Detection. 96-99 - Koichi Miyazaki, Tatsuya Komatsu, Tomoki Hayashi, Shinji Watanabe, Tomoki Toda, Kazuya Takeda:
Conformer-Based Sound Event Detection with Semi-Supervised Learning and Data Augmentation. 100-104 - Filippo Naccari, Ivana Guarneri, Salvatore Curti, Alberto Amilcare Savi:
Embedded Acoustic Scene Classification for Low Power Microcontroller Devices. 105-109 - Khoa Nguyen, Konstantinos Drossos, Tuomas Virtanen:
Temporal Sub-Sampling of Audio Feature Sequences for Automated Audio Captioning. 110-114 - Thi Ngoc Tho Nguyen, Douglas L. Jones, Woon-Seng Gan:
On the Effectiveness of Spatial and Multi-Channel Features for Multi-Channel Polyphonic Sound Event Detection. 115-119 - Thi Ngoc Tho Nguyen, Douglas L. Jones, Woon-Seng Gan:
Ensemble of Sequence Matching Networks for Dynamic Sound Event Localization, Detection, and Tracking. 120-124 - Yuki Okamoto, Keisuke Imoto, Shinnosuke Takamichi, Ryosuke Yamanishi, Takahiro Fukumori, Yoichi Yamashita:
RWCP-SSD-Onomatopoeia: Onomatopoeic Word Dataset for Environmental Sound Synthesis. 125-129 - Kenneth Ooi, Santi Peksi, Woon-Seng Gan:
Ensemble of Pruned Low-Complexity Models for Acoustic Scene Classification. 130-134 - Nicolas Pajusco, Richard Huang, Nicolas Farrugia:
Lightweight Convolutional Neural Networks on Binaural Waveforms for Low Complexity Acoustic Scene Classification. 135-139 - Jihwan Park, Sooyeon Yoo:
DCASE 2020 Task2: Anomalous Sound Detection using Relevant Spectral Feature and Focusing Techniques in the Unsupervised Learning Scenario. 140-144 - Sergi Perez-Castanos, Javier Naranjo-Alcazar, Pedro Zuccarello, Maximo Cobos:
Anomalous Sound Detection using Unsupervised and Semi-Supervised Autoencoders and Gammatone Audio Representation. 145-149 - Sergi Perez-Castanos, Javier Naranjo-Alcazar, Pedro Zuccarello, Maximo Cobos:
Listen Carefully and Tell: An Audio Captioning System Based on Residual Learning and Gammatone Audio Representation. 150-154 - Andrés Pérez-López, Rafael Ibáñez-Usach:
Papafil: A Low Complexity Sound Event Localization and Detection Method with Parametric Particle Filtering and Gradient Boosting. 155-159 - Huy Phan, Lam Pham, Philipp Koch, Ngoc Q. K. Duong, Ian McLoughlin, Alfred Mertins:
On Multitask Loss Function for Audio Event Detection and Localization. 160-164 - Archontis Politis, Sharath Adavanne, Tuomas Virtanen:
A Dataset of Reverberant Spatial Sound Scenes with Moving Sources for Sound Event Localization and Detection. 165-169 - Paul Primus, Verena Haunschmid, Patrick Praher, Gerhard Widmer:
Anomalous Sound Detection as a Simple Binary Classification Problem with Careful Selection of Proxy Outlier Examples. 170-174 - Harsh Purohit, Ryo Tanabe, Takashi Endo, Kaori Suefusa, Yuki Nikaido, Yohei Kawaguchi:
Deep Autoencoding GMM-Based Unsupervised Anomaly Detection in Acoustic Signals and its Hyper-Parameter Optimization. 175-179 - Francesca Ronchini, Daniel Arteaga, Andrés Pérez-López:
Sound Event Localization and Detection Based on CRNN using Rectangular Filters and Channel Rotation Data Augmentation. 180-184 - Saeid Safavi, Turab Iqbal, Wenwu Wang, Philip Coleman, Mark D. Plumbley:
Open-Window: A Sound Event Dataset for Window State Detection and Recognition. 185-189 - Daiki Takeuchi, Yuma Koizumi, Yasunori Ohishi, Noboru Harada, Kunio Kashino:
Effects of Word-Frequency Based Pre- and Post- Processings for Audio Captioning. 190-194 - Noriyuki Tonami, Keisuke Imoto, Takahiro Fukumori, Yoichi Yamashita:
Evaluation Metric of Sound Event Detection Considering Severe Misdetection by Scenes. 195-199 - Nicolas Turpault, Romain Serizel:
Training Sound Event Detection on a Heterogeneous Dataset. 200-204 - Nicolas Turpault, Scott Wisdom, Hakan Erdogan, John R. Hershey, Romain Serizel, Eduardo Fonseca, Prem Seetharaman, Justin Salamon:
Improving Sound Event Detection in Domestic Environments using Sound Separation. 205-209 - Helin Wang, Yuexian Zou, DaDing Chong:
Acoustic Scene Classification with Spectrogram Processing Strategies. 210-214 - Kevin Wilkinghoff:
Using Look, Listen, and Learn Embeddings for Detecting Anomalous Sounds in Machine Condition Monitoring. 215-219 - Yuzhong Wu, Tan Lee:
Searching for Efficient Network Architectures for Acoustic Scene Classification. 220-224 - Xuenan Xu, Heinrich Dinkel, Mengyue Wu, Kai Yu:
A CRNN-GRU Based Reinforcement Learning Approach to Audio Captioning. 225-229 - Liping Yang, Junyong Hao, Zhenwei Hou, Wang Peng:
Two-Stage Domain Adaptation for Sound Event Detection. 230-234 - Hao Yen, Pin-Jui Ku, Ming-Chi Yen, Hung-Shin Lee, Hsin-Min Wang:
Joint Training of Guided Learning and Mean Teacher Models for Sound Event Detection. 235-239 - Pablo Zinemanas, Ignacio Hounie, Pablo Cancela, Frederic Font, Martín Rocamora, Xavier Serra:
DCASE-Models: A Python Library for Computational Environmental Sound Analysis using Deep-Learning Models. 240-244
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