拼音
计算机科学
自然语言处理
语言模型
人工智能
Glyph(数据可视化)
任务(项目管理)
中文
字体
词(群论)
风格(视觉艺术)
汉字
文字嵌入
语音识别
嵌入
语言学
可视化
哲学
管理
考古
经济
历史
作者
Chao Lv,Han Zhang,XinKai Du,Yunhao Zhang,Ying Huang,Wenhao Li,Je-Chin Han,Shen Gu
标识
DOI:10.1109/itaic54216.2022.9836832
摘要
With the success of down streaming task using English pre-trained language model, the pre-trained Chinese language model is also necessary to get better performance of Chinese NLP tasks. Unlike the English language, Chinese has its special characters such as glyph information. So in this article, we propose the Chinese pre-trained language model named StyleBERT which incorporate the following embedding information to enhance the savvy of language model, such as word, pinyin, five stroke and chaizi. The experiments show that the model achieves well performances on a wide range of Chinese NLP tasks.
科研通智能强力驱动
Strongly Powered by AbleSci AI