| 基于全局词汇信息的中文口语句子标点生成 | |
陈萧 ; 柯登峰; 徐波
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| 2013-08 | |
| Conference Name | 全国人机语音通讯学术会议 |
| Source Publication | 第十二届全国人机语音通讯学术会议（NCMMSC'2013）论文集 |
| Conference Date | 5-7 |
| Conference Place | 贵州贵阳 |
| Other Abstract |
Punctuation generation is very important for automatic speech recognition. It greatly improves readability of transcripts and user experience, and facilitates following natural language processing tasks. In this paper, we develop a pure text information based method for punctuation generation for Chinese spoken sentence. The idea is that, first, modeling the relations between global lexical information and punctuation by different segment-level of sentence, then, combining these models using multi-layer perception, final, generating punctuation (period, question mark, exclamation mark). Results indicate that, compared with the baseline, the proposed method results in an 8.9% improvement in un-weighted accuracy and a 4.7% improvement in weighted accuracy. We achieve an un-weighted accuracy of 85.9% and a weighted accuracy of 92.2%. We study the effect on performance of the amount of training data. Results indicate that using larger training data sets consistently improves performance.
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| Keyword | 标点生成 全局信息 词汇信息 模型融合 |
| Document Type | 会议论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/11820 |
| Collection | 数字内容技术与服务研究中心_听觉模型与认知计算 |
| Corresponding Author | 徐波 |
| Affiliation | 中国科学院自动化研究所 |
| Recommended Citation GB/T 7714 | 陈萧,柯登峰,徐波. 基于全局词汇信息的中文口语句子标点生成[C],2013. |
| Files in This Item: | Download All | |||||
| File Name/Size | DocType | Version | Access | License | ||
| 2013NCMMSC.pdf（188KB） | 会议论文 | 开放获取 | CC BY-NC-SA | View Download | ||
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