69 citations · 144 across the 22 of their papers we have counts for
4 papers · 1 filter
Spatial mixup: Directional loudness modification as data augmentation for sound event localization and detection
Ricardo Falcon-Perez, Kazuki Shimada, Yuichiro Koyama +2
Data augmentation methods have shown great importance in diverse supervised learning problems where labeled data is scarce or costly to obtain. For sound event localization and det…
Multi-ACCDOA: Localizing and Detecting Overlapping Sounds from the Same Class with Auxiliary Duplicating Permutation Invariant Training
Kazuki Shimada, Yuichiro Koyama, Shusuke Takahashi +3
Sound event localization and detection (SELD) involves identifying the direction-of-arrival (DOA) and the event class. The SELD methods with a class-wise output format make the mod…
Spatial Data Augmentation with Simulated Room Impulse Responses for Sound Event Localization and Detection
Yuichiro Koyama, Kazuhide Shigemi, Masafumi Takahashi +5
Recording and annotating real sound events for a sound event localization and detection (SELD) task is time consuming, and data augmentation techniques are often favored when the a…
Ensemble of ACCDOA- and EINV2-based Systems with D3Nets and Impulse Response Simulation for Sound Event Localization and Detection
Kazuki Shimada, Naoya Takahashi, Yuichiro Koyama +4
This report describes our systems submitted to the DCASE2021 challenge task 3: sound event localization and detection (SELD) with directional interference. Our previous system base…