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 limit 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 the 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.
A Stutter Seldom Comes Alone -- Cross-Corpus Stuttering Detection as a Multi-label Problem
Technische Hochschule Nürnberg Georg Simon Ohm（纽伦堡乔治·西蒙·欧姆应用技术大学）；KST Institut GmbH（KST研究所有限公司）；Intel Labs（英特尔实验室）；Friedrich-Alexander-Universität Erlangen-Nürnberg（埃尔朗根-纽伦堡弗里德里希-亚历山大大学）
An Improved Event-Independent Network for Polyphonic Sound Event Localization and Detection
Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey（萨里大学视觉、语音与信号处理中心（CVSSP））；ByteDance（字节跳动）；Qingdao University of Technology（青岛理工大学）
Active noise cancellation on open-ear smart glasses
Department of Electrical and Computer Engineering, Carnegie Mellon University（卡内基梅隆大学电气与计算机工程系）；Department of Medical Physics and Acoustics, Carl von Ossietzky Universität Oldenburg（奥尔登堡大学医学物理与声学系）；College of Computer Science and Technology, Zhejiang University（浙江大学计算机科学与技术学院）
MAGENTA: Magnitude and Geometry-Enhanced Training Approach for Long-Tailed Sound Event Localization and Detection
Smart Nation TRANS Lab, School of Electrical and Electronic Engineering（智能国家TRANS实验室，电子与电气工程学院）；Nanyang Technological University, Singapore（南洋理工大学，新加坡）
SwG-former: A Sliding-Window Graph Convolutional Network for Simultaneous Spatial-Temporal Information Extraction in Sound Event Localization and Detection
