Search Results for author: Kazuki Shimada

Found 7 papers, 4 papers with code

STARSS22: A dataset of spatial recordings of real scenes with spatiotemporal annotations of sound events

2 code implementations4 Jun 2022 Archontis Politis, Kazuki Shimada, Parthasaarathy Sudarsanam, Sharath Adavanne, Daniel Krause, Yuichiro Koyama, Naoya Takahashi, Shusuke Takahashi, Yuki Mitsufuji, Tuomas Virtanen

Additionally, the report presents the baseline system that accompanies the dataset in the challenge with emphasis on the differences with the baseline of the previous iterations; namely, introduction of the multi-ACCDOA representation to handle multiple simultaneous occurences of events of the same class, and support for additional improved input features for the microphone array format.

Sound Event Localization and Detection

Metric Learning with Background Noise Class for Few-shot Detection of Rare Sound Events

no code implementations30 Oct 2019 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.

Few-Shot Learning Metric Learning

Unsupervised Speech Enhancement Based on Multichannel NMF-Informed Beamforming for Noise-Robust Automatic Speech Recognition

no code implementations22 Mar 2019 Kazuki Shimada, Yoshiaki Bando, Masato Mimura, Katsutoshi Itoyama, Kazuyoshi Yoshii, Tatsuya Kawahara

To solve this problem, we take an unsupervised approach that decomposes each TF bin into the sum of speech and noise by using multichannel nonnegative matrix factorization (MNMF).

Automatic Speech Recognition Speech Enhancement +1

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