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ORCID7th DCASE 2022: Nancy, France
- Mathieu Lagrange, Annamaria Mesaros, Thomas Pellegrini, Gaël Richard, Romain Serizel, Dan Stowell:
Proceedings of the 7th Workshop on Detection and Classification of Acoustic Scenes and Events 2022, DCASE 2022, Nancy, France, November 3-4, 2022. Tampere University 2022, ISBN 978-952-03-2677-7 - Kimberly T. Mai, Toby Davies, Lewis D. Griffin, Emmanouil Benetos:
Explaining the Decision of Anomalous Sound Detectors. - Helin Wang, Dongchao Yang, Yuexian Zou, Fan Cui, Yujun Wang:
Detect What You Want: Target Sound Detection. - Yufeng Deng, Anbai Jiang, Yuchen Duan, Jitao Ma, Xuchu Chen, Jia Liu, Pingyi Fan, Cheng Lu, Wei-Qiang Zhang:
Ensemble of Multiple Anomalous Sound Detectors. - Jinhua Liang, Huy Phan, Emmanouil Benetos:
Leveraging Label Hierachies for Few-Shot Everyday Sound Recognition. - Dominique Fourer, Agnieszka Orlowska:
Detection and Identification of Beehive Piping Audio Signals. - Yiming Li, Zhifang Guo, Zhirong Ye, Xiangdong Wang, Hong Liu, Yueliang Qian, Rui Tao, Long Yan, Kazushige Ouchi:
A Hybrid System of Sound Event Detection Transformer and Frame-Wise Model for DCASE 2022 Task 4. - Slawomir Kapka, Jakub Tkaczuk:
CoLoC: Conditioned Localizer and Classifier for Sound Event Localization and Detection. - Alberto García Arroba Parrilla, Dan Stowell:
Polyphonic Sound Event Detection for Highly Dense Birdsong Scenes. - John Martinsson, Martin Willbo, Aleksis Pirinen, Olof Mogren, Maria Sandsten:
Few-Shot Bioacoustic Event Detection Using an Event-Length Adapted Ensemble of Prototypical Networks. - Inês Nolasco, Shubhr Singh, E. Vidaña-Villa, Emily Grout, J. Morford, Michael G. Emmerson, Frants H. Jensen, Ivan Kiskin, Helen Whitehead, Ariana Strandburg-Peshkin, Lisa F. Gill, Hanna Pamula, Vincent Lostanlen, Veronica Morfi, Dan Stowell:
Few-Shot Bioacoustic Event Detection at the DCASE 2022 Challenge. - Haohe Liu, Xubo Liu, Xinhao Mei, Qiuqiang Kong, Wenwu Wang, Mark D. Plumbley:
Segment-Level Metric Learning for Few-Shot Bioacoustic Event Detection. - Joo-Hyun Lee, Jeong-Hwan Choi, Pil Moo Byun, Joon-Hyuk Chang:
Multi-Scale Architecture and Device-Aware Data-Random-Drop Based Fine-Tuning Method for Acoustic Scene Classification. - Enis Berk Çoban, Megan Perra, Dara Pir, Michael I. Mandel:
EDANSA-2019: The Ecoacoustic Dataset from Arctic North Slope Alaska. - Rohith Mars, Rohan Kumar Das:
A Device Classification-Aided Multi-Task Framework for Low-Complexity Acoustic Scene Classification. - Dongchao Yang, Helin Wang, Wenwu Wang, Yuexian Zou:
A Mixed Supervised Learning Framework For Target Sound Detection. - Robin Scheibler, Tatsuya Komatsu, Yusuke Fujita, Michael Hentschel:
Sound Event Localization and Detection with Pre-Trained Audio Spectrogram Transformer and Multichannel Seperation Network. - Kai Li, Quoc-Huy Nguyen, Yasuji Ota, Masashi Unoki:
Unsupervised Anomalous Sound Detection for Machine Condition Monitoring Using Temporal Modulation Features on Gammatone Auditory Filterbank. - Florian Schmid, Shahed Masoudian, Khaled Koutini, Gerhard Widmer:
Knowledge Distillation from Transformers for Low-Complexity Acoustic Scene Classification. - Thomas Pellegrini:
Language-Based Audio Retrieval with Textual Embeddings of Tag Names. - Ismail Nejjar, Jean Meunier-Pion, Gaëtan Frusque, Olga Fink:
DG-Mix: Domain Generalization for Anomalous Sound Detection Based on Self-Supervised Learning. - Irene Martín-Morató, Francesco Paissan, Alberto Ancilotto, Toni Heittola, Annamaria Mesaros, Elisabetta Farella, Alessio Brutti, Tuomas Virtanen:
Low-Complexity Acoustic Scene Classification in DCASE 2022 Challenge. - Arshdeep Singh, Mark D. Plumbley:
Low-Complexity CNNs for Acoustic Scene Classification. - Mohamed Outidrarine, Pierre Baudet, Vincent Lostanlen, Mathieu Lagrange, Juan Sebastian Ulloa:
Exploring Eco-Acoustic Data with K-Determinantal Point Processes. - Irene Martín-Morató, Manu Harju, Annamaria Mesaros:
A Summarization Approach to Evaluating Audio Captioning. - Paul Primus, Gerhard Widmer:
Improving Natural-Language-Based Audio Retrieval with Transfer Learning and Audio & Text Augmentations. - Wim Boes, Hugo Van hamme:
Impact of Temporal Resolution on Convolutional Recurrent Networks for Audio Tagging and Sound Event Detection. - Satvik Venkatesh, Gordon Wichern, Aswin Shanmugam Subramanian, Jonathan Le Roux:
Improved Domain Generalization via Disentangled Multi-Task Learning in Unsupervised Anomalous Sound Detection. - Etienne Labbé, Thomas Pellegrini, Julien Pinquier:
Is my Automatic Audio Captioning System so Bad? SPIDEr-max: A Metric to Consider Several Caption Candidates. - Yang Xiao, Xubo Liu, James A. King, Arshdeep Singh, Eng Siong Chng, Mark D. Plumbley, Wenwu Wang:
Continual Learning for On-Ddevice Environmental Sound Classification. - Andrea Napoli, Paul R. White, Thomas Blumensath:
Quantity Over Quality? Investigating the Effects of Volume and Strength of Training Data in Marine Bioacoustics. - Ren Li, Jinhua Liang, Huy Phan:
Few-Shot Bioacoustic Event Detection: Enhanced Classifiers for Prototypical Networks. - Archontis Politis, Kazuki Shimada, Parthasaarathy Sudarsanam, Sharath Adavanne, Daniel Krause, Yuichiro Koyama, Naoya Takahashi, Shusuke Takahashi, Yuki Mitsufuji, Tuomas Virtanen:
STARSS22: A Dataset of Spatial Recordings of Real Scenes with Spatiotemporal Annotations of Sound Events. - Saksham Singh Kushwaha, Irán R. Román, Juan Pablo Bello:
Analyzing the Effect of Equal-Angle Spatial Discretization on Sound Event Localization and Detection. - David Perera, Slim Essid, Gaël Richard:
Latent and Adversarial Data Augmentations for Sound Event Detection and Classification. - Huang Xie, Samuel Lipping, Tuomas Virtanen:
Language-Based Audio Retrieval Task in DCASE 2022 Challenge. - Lorenz P. Schmidt, Beran Kiliç, Nils Peters:
Feature Selection Using Alternating Direction Method of Multiplier for Low-Complexity Acoustic Scene Classification. - Jinbo Hu, Yin Cao, Ming Wu, Qiuqiang Kong, Feiran Yang, Mark D. Plumbley, Jun Yang:
Sound Event Localization and Detection for Real Spatial Sound Scenes: Event-Independent Network and Data Augmentation Chains. - Kota Dohi, Tomoya Nishida, Harsh Purohit, Ryo Tanabe, Takashi Endo, Masaaki Yamamoto, Yuki Nikaido, Yohei Kawaguchi:
MIMII DG: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection for Domain Ggeneralization Task. - Kota Dohi, Keisuke Imoto, Noboru Harada, Daisuke Niizumi, Yuma Koizumi, Tomoya Nishida, Harsh Purohit, Ryo Tanabe, Takashi Endo, Masaaki Yamamoto, Yohei Kawaguchi:
Description and Discussion on DCASE 2022 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring Applying Domain Generalization Techniques. - Rie Koga, Sawa Takamuku, Keisuke Imoto, Naotake Natori:
Model Training that Prioritizes Rare Overlapped Labels for Polyphonic Sound Event Detection. - Won-Gook Choi, Joon-Hyuk Chang:
Confidence Regularized Entropy for Polyphonic Sound Event Detection. - Francesca Ronchini, Samuele Cornell, Romain Serizel, Nicolas Turpault, Eduardo Fonseca, Daniel P. W. Ellis:
Description and Analysis of Novelties Introduced in DCASE Task 4 2022 on the Baseline System. - François Effa, Romain Serizel, Jean-Pierre Arz, Nicolas Grimault:
Convolutional Neural Network for Audibility Assessment of Acoustic Alarms. - Mohammad Abdollahi, Romain Serizel, Alain Rakotomamonjy, Gilles Gasso:
Integrating Isolated Examples with Weakly-Supervised Sound Event Detection: A Direct Approach. - Benno Weck, Miguel Pérez Fernández, Holger Kirchhoff, Xavier Serra:
Matching Text and Audio Embeddings: Exploring Transfer-Learning Strategies for Language-Based Audio Retrieval.
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