7 citations · 21 across the 15 of their papers we have counts for
17 papers
Self-supervised learning method using multiple sampling strategies for general-purpose audio representation
Ibuki Kuroyanagi, Tatsuya Komatsu
We propose a self-supervised learning method using multiple sampling strategies to obtain general-purpose audio representation. Multiple sampling strategies are used in the propose…
How Information on Acoustic Scenes and Sound Events Mutually Benefits Event Detection and Scene Classification Tasks
Keisuke Imoto, Yuka Komatsu, Shunsuke Tsubaki +1
Acoustic scene classification (ASC) and sound event detection (SED) are fundamental tasks in environmental sound analysis, and many methods based on deep learning have been propose…
Better Intermediates Improve CTC Inference
Tatsuya Komatsu, Yusuke Fujita, Jaesong Lee +3
This paper proposes a method for improved CTC inference with searched intermediates and multi-pass conditioning. The paper first formulates self-conditioned CTC as a probabilistic…
InterAug: Augmenting Noisy Intermediate Predictions for CTC-based ASR
Yu Nakagome, Tatsuya Komatsu, Yusuke Fujita +2
This paper proposes InterAug: a novel training method for CTC-based ASR using augmented intermediate representations for conditioning. The proposed method exploits the conditioning…
Non-Autoregressive ASR with Self-Conditioned Folded Encoders
Tatsuya Komatsu
This paper proposes CTC-based non-autoregressive ASR with self-conditioned folded encoders. The proposed method realizes non-autoregressive ASR with fewer parameters by folding the…
Acoustic Event Detection with Classifier Chains
Tatsuya Komatsu, Shinji Watanabe, Koichi Miyazaki +1
This paper proposes acoustic event detection (AED) with classifier chains, a new classifier based on the probabilistic chain rule. The proposed AED with classifier chains consists…