Libri-adhoc40: A dataset collected from synchronized ad-hoc microphone arrays
Abstract
Recently, there is a research trend on ad-hoc microphone arrays. However, most research was conducted on simulated data. Although some data sets were collected with a small number of distributed devices, they were not synchronized which hinders the fundamental theoretical research to ad-hoc microphone arrays. To address this issue, this paper presents a synchronized speech corpus, named Libri-adhoc40, which collects the replayed Librispeech data from loudspeakers by ad-hoc microphone arrays of 40 strongly synchronized distributed nodes in a real office environment. Besides, to provide the evaluation target for speech frontend processing and other applications, we also recorded the replayed speech in an anechoic chamber. We trained several multi-device speech recognition systems on both the Libri-adhoc40 dataset and a simulated dataset. Experimental results demonstrate the validness of the proposed corpus which can be used as a benchmark to reflect the trend and difference of the models with different ad-hoc microphone arrays. The dataset is online available at https://github.com/ISmallFish/Libri-adhoc40.
Keywords
Cite
@article{arxiv.2103.15118,
title = {Libri-adhoc40: A dataset collected from synchronized ad-hoc microphone arrays},
author = {Shanzheng Guan and Shupei Liu and Junqi Chen and Wenbo Zhu and Shengqiang Li and Xu Tan and Ziye Yang and Menglong Xu and Yijiang Chen and Jianyu Wang and Xiao-Lei Zhang},
journal= {arXiv preprint arXiv:2103.15118},
year = {2021}
}