The XMUSPEECH System for Accented English Automatic Speech Recognition

被引：2
|
作者：
Tong, Fuchuan [1 ]
Li, Tao [2 ]
Liao, Dexin [2 ]
Xia, Shipeng [2 ]
Li, Song [1 ]
Hong, Qingyang [2 ]
Li, Lin [1 ]
机构：
[1] Xiamen Univ, Sch Elect Sci & Engn, Xiamen 361005, Peoples R China
[2] Xiamen Univ, Sch Informat, Xiamen 361005, Peoples R China
来源：
APPLIED SCIENCES-BASEL | 2022年 / 12卷 / 03期
基金：
中国国家自然科学基金;
关键词：
AESRC2020; i-vector; x-vector; multistream CNN;
D O I：
10.3390/app12031478
中图分类号：
O6 [化学];
学科分类号：
0703 ;
摘要：
In this paper, we present the XMUSPEECH systems for Track 2 of the Interspeech 2020 Accented English Speech Recognition Challenge (AESRC2020). Track 2 is an Automatic Speech Recognition (ASR) task where the non-native English speakers have various accents, which reduces the accuracy of the ASR system. To solve this problem, we experimented with acoustic models and input features. Furthermore, we trained a TDNN-LSTM language model for lattice rescoring to obtain better results. Compared with our baseline system, we achieved relative word error rate (WER) improvements of 40.7% and 35.7% on the development set and evaluation set, respectively.
引用
收藏
页数：8
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