69 citations · 144 across the 22 of their papers we have counts for
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eess.AS2019
Metric Learning with Background Noise Class for Few-shot Detection of Rare Sound Events
Kazuki Shimada, Yuichiro Koyama, Akira Inoue
Few-shot learning systems for sound event recognition have gained interests since they require only a few examples to adapt to new target classes without fine-tuning. However, such…
cs.SD2019★ 69 cited
Unsupervised Speech Enhancement Based on Multichannel NMF-Informed Beamforming for Noise-Robust Automatic Speech Recognition
Kazuki Shimada, Yoshiaki Bando, Masato Mimura +3
This paper describes multichannel speech enhancement for improving automatic speech recognition (ASR) in noisy environments. Recently, the minimum variance distortionless response…