@inproceedings{6560a124b2ae4a77b2e2e932d52ddc6a,
title = "HelloNPU: A corpus for small-footprint wake-up word detection research",
abstract = "As the first very step to activate speech interfaces, wake-up word detection aims to achieve a fully hand-free experience by detecting a specific word or phrase to activate the speech recognition and understanding modules. The task usually requires low-latency, highly accurate, small-footprint and easily migratory to power limited environment. In this paper, we describe the creation of HelloNPU, a publicly-available corpus that provides a common testbed to facilitate wake-up word detection research. We also introduce some baseline experimental results on this proposed corpus using the deep KWS approach. We hope the release of this corpus can trigger more studies on small-footprint wake-up word detection.",
keywords = "Deep neural network, Keyword spotting, Wake-up word detection",
author = "Senmao Wang and Jingyong Hou and Lei Xie and Yufeng Hao",
note = "Publisher Copyright: {\textcopyright} 2018, Springer Nature Singapore Pte Ltd.; 14th National Conference on Man-Machine Speech Communication, NCMMSC 2017 ; Conference date: 11-10-2017 Through 13-10-2017",
year = "2018",
doi = "10.1007/978-981-10-8111-8_7",
language = "英语",
isbn = "9789811081101",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "70--79",
editor = "Ya Li and Zheng, {Thomas Fang} and Changchun Bao and Dong Wang and Jianhua Tao",
booktitle = "Man-Machine Speech Communication - 14th National Conference, NCMMSC 2017, Revised Selected Papers",
}