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KanuriSenti:在资源不足的Kanuri语言中进行情绪分析的新型数据集

Bashir Maina Saleh¹, Saurabh Bilgaiyan¹, Santwana Sagnika¹

¹School of Computer Engineering, KIIT, Deemed to be University, Bhubaneswar, Odisha, 751024, India.

|July 4, 2025

概括

这项研究介绍了KanuriSenti,这是一个用于Kanuri语言的新情感分析数据集. 这种资源有助于自然语言处理资源不足的非洲语言.

科学领域:

计算语言学计算语言学
自然语言处理自然语言处理.
非洲语言非洲语言

背景情况:

坎努里语是尼日利亚和得湖地区的主要语言,但在自然语言处理 (NLP) 中仍然缺乏资源.
现有的NLP资源缺乏对Kanuri进行结构化,情绪注释的数据,阻碍了研究和开发.
这种差距限制了为Kanuri讲者创建有效的情感分析工具.

研究的目的:

为了介绍KanuriSenti,一个新的情感分析数据集为Kanuri语言.
为低资源环境中情绪分析研究提供有价值的资源.
支持非洲平等语言技术的发展.

主要方法:

开发了一个基于词典的数据集,包含超过10,000个Kanuri条目,标记为情绪极性 (积极,消极,中立).
创建了一个情感的E-ANEW风格的数据集,注释了本地Kanuri说话者对Valence, Arousal和Dominance的注释.
通过Cohen's Kappa验证了注释一致性,并通过Type-Token Ratio测量了词汇丰富性.

主要成果:

KanuriSenti包括一个基于词典的情感数据集和一个情感维度数据集.
通过科恩的卡帕证实了注释可靠性,并且建立了词汇丰富性.
该数据集适用于各种情绪分析任务和基准.

结论:

KanuriSenti对资源不足的语言的NLP做出了重大贡献.
该数据集作为一个基准,用于评估在低资源环境中的情绪分析模型.
这项工作促进了非洲的公平语言技术发展.

关键词:

卡努里数据集卡努里数据集资源较少的语言资源较少的语言在NLP中,我们使用了NLP.人们的论挖掘.情绪分析是一种情绪分析.资源不足的语言资源不足的语言

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