计算机BIOPAC系统韵律与呼吸的交互关系——上海话与普通话

IF 0.9 4区计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Intelligent Data Analysis Pub Date : 2023-08-31 DOI:10.3233/ida-237443

Xiaohong Meng, Zhongxiu Yang, Zhi Li

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引用次数: 0

摘要

本文利用计算机BIOPAC系统工具对上海话和普通话阅读寓言中韵律与呼吸的关系进行了分析，得出以下结论：1）呼吸参数的均值与呼吸单位呈正相关，上海话的呼吸曲线表现出小起伏的特点，与普通话的呼吸曲线不同；2）呼吸的重置与静音段有关，重置呼吸部位的发生必须有一个安静期，而不发生相反的情况；3）在寓言文体具有柔性特征的情境下，文本的熟练程度可以显著增加呼吸曲线的复杂性，呈现出更为特殊的特征，如呼吸音。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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The interactive relationship between prosody and respiration of computer BIOPAC systems: Shanghai dialect and mandarin

This paper uses the computer BIOPAC Systems tool to analyze Shanghai dialect and Mandarin which refers to the relationship between prosody and respiration in reading fable, the conclusion are as follows: 1) the mean of respiratory parameters and respiratory units was positively related, and respiration curve on Shanghai dialect which shows the characteristics of small ups and downs is different from the Mandarin curve; 2) the reset of respiration has relationship with mute segment, and the occurrence of reset breathing place must have a quiet period, while the opposite does not happen; 3) on the situation of fable literary style with flexible feature, the text of the proficiency can significantly increase the complexity of the respiration curve, showing a more special features such as “breathless” pronunciation.

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来源期刊

Intelligent Data Analysis 工程技术-计算机：人工智能

CiteScore

2.20

自引率

5.90%

发文量

审稿时长

3.3 months

期刊介绍： Intelligent Data Analysis provides a forum for the examination of issues related to the research and applications of Artificial Intelligence techniques in data analysis across a variety of disciplines. These techniques include (but are not limited to): all areas of data visualization, data pre-processing (fusion, editing, transformation, filtering, sampling), data engineering, database mining techniques, tools and applications, use of domain knowledge in data analysis, big data applications, evolutionary algorithms, machine learning, neural nets, fuzzy logic, statistical pattern recognition, knowledge filtering, and post-processing. In particular, papers are preferred that discuss development of new AI related data analysis architectures, methodologies, and techniques and their applications to various domains.