ASMSP-SS2.1
HOW MUCH DOES MACHINE IDENTITY MATTER IN ANOMALOUS SOUND DETECTION AT TEST TIME?
Kevin Wilkinghoff, Aalborg University/Pioneer Centre for AI, Denmark; Keisuke Imoto, Kyoto University, Japan; Zheng-Hua Tan, Aalborg University/Pioneer Centre for AI, Denmark
Session:
Sound of Change – Advances in Acoustic Anomaly Detection Lecture
Track:
20: Sound of Change – Advances in Acoustic Anomaly Detection
Location:
Forum 6
Session Time:
Thu, 3 Sep, 10:30 - 12:10
Presentation Time:
Thu, 3 Sep, 10:30 - 10:50
Session Co-Chairs:
Tomoya Nishida, Hitachi and Keisuke Imoto, Kyoto University
Presentation
Discussion
Session ASMSP-SS2
ASMSP-SS2.1: HOW MUCH DOES MACHINE IDENTITY MATTER IN ANOMALOUS SOUND DETECTION AT TEST TIME?
Kevin Wilkinghoff, Aalborg University/Pioneer Centre for AI, Denmark; Keisuke Imoto, Kyoto University, Japan; Zheng-Hua Tan, Aalborg University/Pioneer Centre for AI, Denmark
ASMSP-SS2.2: MEMNMF: MEMORY-AUGMENTED NMF ON LPC SPECTRA FOR ANOMALOUS SOUND DETECTION
Phurich Saengthong, Takahiro Shinozaki, Institute of Science Tokyo, Japan
ASMSP-SS2.3: SPIKE BASED APPROACH FOR ANOMALY LOCALIZATION IN LENGTHY BIOACOUSTIC RECORDINGS
Sarangan Raveendranathan, Prasanga N. Samarasinghe, Thushara D. Abhayapala, The Australian National University, Australia
ASMSP-SS2.4: Generalized Zero-Shot Learning of Acoustic Event Using Attribute-Conditioned GAN and Out-of-Distribution Detector
Kohei Uehara, Kobe University, Japan; Ryoichi Takashima, Ritsumeikan University, Japan; Tetsuya Takiguchi, Kobe University, Japan
ASMSP-SS2.5: Inter-Audio Diverse Decoding for Audio Difference Captioning in Unsupervised Anomalous Sound Detection Scenarios
Tomoya Nishida, Yusuke Kanamori, Harsh Purohit, Kota Dohi, Takashi Endo, Yohei Kawaguchi, Hitachi, ltd., Japan
Resources
No resources available.