@inproceedings{e65fa2f4bbad478d97f99987157a2bb8,
title = "The accented English speech recognition challenge 2020: Open datasets, tracks, baselines, results and methods",
abstract = "The variety of accents has posed a big challenge to speech recognition. The Accented English Speech Recognition Challenge (AESRC2020) is designed for providing a common testbed and promoting accent-related research. Two tracks are set in the challenge - English accent recognition (track 1) and accented English speech recognition (track 2). A set of 160 hours of accented English speech collected from 8 countries is released with labels as the training set. Another 20 hours of speech without labels is later released as the test set, including two unseen accents from another two countries used to test the model generalization ability in track 2. We also provide baseline systems for the participants. This paper first reviews the released dataset, track setups, baselines and then summarizes the challenge results and major techniques used in the submissions.",
keywords = "Accent recognition, Accented speech recognition, Acoustic modeling, End-to-end ASR",
author = "Xian Shi and Fan Yu and Yizhou Lu and Yuhao Liang and Qiangze Feng and Daliang Wang and Yanmin Qian and Lei Xie",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE; 2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 ; Conference date: 06-06-2021 Through 11-06-2021",
year = "2021",
doi = "10.1109/ICASSP39728.2021.9413386",
language = "英语",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "6918--6922",
booktitle = "2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 - Proceedings",
}