SS5.4
Aggregation Strategies for Efficient Annotation of Bioacoustic Sound Events Using Active Learning
Richard Lindholm, Oscar Marklund, Lund University, Sweden; Olof Mogren, RISE Research Institutes of Sweden, Climes - Swedish Centre for Impacts of Climate Extremes, Climate AI Nordics, Sweden; John Martinsson, Lund University, RISE Research Institutes of Sweden, Climate AI Nordics, Sweden
Session:
SS5: Acoustic Scene Analysis and Signal Enhancement Based on Advanced Signal Processing and Machine Learning Lecture
Track:
Special Sessions
Location:
Teatro del Sole
Presentation Time:
Tue, 9 Sep, 17:00 - 17:20 Italy Time (UTC +2)
Session Co-Chairs:
Shoji Makino, Waseda University and Nobutaka Ono, Tokyo Metropolitan University
Presentation
Discussion
Resources
No resources available.
Session SS5
SS5.1: Multi-Microphone and Multi-Modal Emotion Recognition in Reverberant Environment
Ohad Cohen, Gershon Hazan, Sharon Gannot, Bar-Ilan University, Israel
SS5.2: DIFFCBF: A DIFFUSION MODEL WITH CONVOLUTIONAL BEAMFORMER FOR JOINT SPEECH SEPARATION, DENOISING, AND DEREVERBERATION
Rino Kimura, Tetsuya Ueda, Waseda University, Japan; Tomohiro Nakatani, Naoyuki Kamo, Marc Delcroix, Shoko Araki, NTT Corporation, Japan; Shoji Makino, Waseda University, Japan
SS5.3: WARPING: DATA-DRIVEN MIXTURE PREPROCESSING TO BOOST THE PERFORMANCE OF BLIND SPEECH SEPARATION
Jiri Malek, Zbynek Koldovsky, Jaroslav Cmejla, Technical University of Liberec, Czech Republic
SS5.4: Aggregation Strategies for Efficient Annotation of Bioacoustic Sound Events Using Active Learning
Richard Lindholm, Oscar Marklund, Lund University, Sweden; Olof Mogren, RISE Research Institutes of Sweden, Climes - Swedish Centre for Impacts of Climate Extremes, Climate AI Nordics, Sweden; John Martinsson, Lund University, RISE Research Institutes of Sweden, Climate AI Nordics, Sweden
SS5.5: Domain Adaptation for Multi-Channel Acoustic Scene Classification to Different Array Positions
Takao Kawamura, Yoshiki Masuyama, Nobutaka Ono, Tokyo Metropolitan University, Japan