EMBEDDED LARGE-SCALE HANDWRITTEN CHINESE CHARACTER RECOGNITION

被引:0
|
作者
Chherawala, Youssouf [1 ]
Dolfing, Hans J. G. A. [1 ]
Dixon, Ryan S. [1 ]
Bellegarda, Jerome R. [1 ]
机构
[1] Apple Inc, Cupertino, CA 95014 USA
来源
2020 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING | 2020年
关键词
Chinese handwriting recognition; style diversity; neural architecture optimization; mobile devices; ONLINE;
D O I
暂无
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
As handwriting input becomes more prevalent, the large symbol inventory required to support Chinese handwriting recognition poses unique challenges. This paper describes how the Apple deep learning recognition system can accurately handle up to 30,000 Chinese characters while running in real-time across a range of mobile devices. To achieve acceptable accuracy, we paid particular attention to data collection conditions, representativeness of writing styles, and training regimen. We found that, with proper care, even larger inventories are within reach. Our experiments show that accuracy only degrades slowly as the inventory increases, as long as we use training data of sufficient quality and in sufficient quantity.
引用
收藏
页码:8169 / 8173
页数:5
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