Chapitres
- A DEVICE CLASSIFICATION-AIDED MULTI-TASK FRAMEWORK FOR LOW-COMPLEXITY ACOUSTIC SCENE CLASSIFICATION
- Knowledge Distillation from Transformers for Low-Complexity Acoustic Scene Classification
- SOUND EVENT LOCALIZATION AND DETECTION WITH PRE-TRAINED AUDIO SPECTROGRAM TRANSFORMER...
- Detection and Identification of Beehive Piping Audio Signals
- Few-shot bioacoustic event detection using an event-length adapted ensemble of prototypical networks
- Sound event localization and detection for real spatial sound scenes: event-independent network...
- Convolutional Neural Network for audibility assessment of acoustic alarms
- Language-based audio retrieval with textual embeddings of tag names
DCASE2022 Workshop
Workshop on Detection and Classification of Acoustic Scenes and Events
Poster spotlights 4
A DEVICE CLASSIFICATION-AIDED MULTI-TASK FRAMEWORK FOR LOW-COMPLEXITY ACOUSTIC SCENE CLASSIFICATION
Rohith Mars, Rohan Kumar Das
Knowledge Distillation from Transformers for Low-Complexity Acoustic Scene Classification
Florian Schmid, Shahed Masoudian, Khaled Koutini, Gerhard Widmer
CONFIDENCE REGULARIZED ENTROPY FOR POLYPHONIC SOUND EVENT DETECTION
Won-GookChoi, Joon-Hyuk Chang
SOUND EVENT LOCALIZATION AND DETECTION WITH PRE-TRAINED AUDIO SPECTROGRAM TRANSFORMER AND MULTICHANNEL SEPARATION NETWORK
Robin Scheibler, Tatsuya Komatsu, Yusuke Fujita, Michael Hentschel
Detection and Identification of Beehive Piping Audio Signals
Dominique Fourer, Agnieszka Orlowska
Few-shot bioacoustic event detection using an event-length adapted ensemble of prototypical networks
John Martinsson, Martin Willbo, Aleksis Pirinen, Olof Mogren, Maria Sandsten
Sound event localization and detection for real spatial sound scenes: event-independent network and data augmentation chains
Jinbo Hu, Yin Cao, Ming Wu, Qiuqiang Kong, Feiran Yang, Mark D. Plumbley, Jun Yang
Explaining the Decisions of Anomalous Sound Detectors
Kimberly T. Mai, Toby Davies, Lewis Griffin, Emmanouil Benetos
ENSEMBLE OF MULTIPLE ANOMALOUS SOUND DETECTORS
Yufeng Deng, Anbai Jiang, Yuchen Duan, Jitao Ma, Xuchu Chen, Jia Liu, Pingyi Fan, Cheng Lu, Wei-Qiang Zhang
Convolutional Neural Network for audibility assessment of acoustic alarms
François Effa, Romain Serizel, Jean-Pierre Arz, Nicolas Grimault
Language-based audio retrieval with textual embeddings of tag names
Thomas Pellegrini
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The workshop aims to provide a venue for researchers working on computational analysis of sound events and scene analysis to present and discuss their results.
The 7th Workshop on Detection and Classification of Acoustic Scenes and Events, DCASE 2022, will be held in Nancy on November 3-4. The event will be held in presence with oral talks being broadcasted.
As in previous years the workshop is organized in conjunction with the DCASE challenge. We aim to bring together researchers from many different universities and companies with an interest in the topic, and provide the opportunity for scientific exchange of ideas and opinions.
The technical program will include invited speakers on the topic of computational everyday sound analysis and recognition, and oral and poster presentations of accepted papers. Additionally, a special poster session will be dedicated to the DCASE 2022 challenge entries and results.
Informations
- Nicolas Duquennoy
- 21 novembre 2022 17:15
- Colloques et Conférences
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