WEARABLE SELD DATASET: DATASET FOR SOUND EVENT LOCALIZATION AND DETECTION USING WEARABLE DEVICES AROUND HEAD

Kento Nagatomo, Masahiro Yasuda, Kohei Yatabe, Shoichiro Saito, Yasuhiro Oikawa

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Sound event localization and detection (SELD) is a combined task of identifying the sound event and its direction. Deep neural networks (DNNs) are utilized to associate them with the sound signals observed by a microphone array. Although ambisonic microphones are popular in the literature of SELD, they might limits the range of applications due to their predetermined geometry. Some applications (including those for pedestrians that perform SELD while walking) require a wearable microphone array whose geometry can be designed to suit the task. In this paper, for development of such a wearable SELD, we propose a dataset named Wearable SELD dataset. It consists of data recorded by 24 microphones placed on a head and torso simulators (HATS) with some accessories mimicking wearable devices (glasses, earphones, and headphones). We also provide experimental results of SELD using the proposed dataset and SELDNet to investigate the effect of microphone configuration.

本文言語English
ホスト出版物のタイトル2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ページ156-160
ページ数5
ISBN(電子版)9781665405409
DOI
出版ステータスPublished - 2022
イベント47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Virtual, Online, Singapore
継続期間: 2022 5月 232022 5月 27

出版物シリーズ

名前ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
2022-May
ISSN(印刷版)1520-6149

Conference

Conference47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022
国/地域Singapore
CityVirtual, Online
Period22/5/2322/5/27

ASJC Scopus subject areas

  • ソフトウェア
  • 信号処理
  • 電子工学および電気工学

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