一个数据集的合成艺术对话与ChatGPT
Manuel Gil-Martín1, Cristina Luna-Jiménez2, Sergio Esteban-Romero2
1Speech Technology and Machine Learning Group (T.H.A.U. Group), Information Processing and Telecommunications Center, E.T.S.I. de Telecomunicación, Universidad Politécnica de Madrid, 28040, Madrid, Spain. manuel.gilmartin@upm.es.
Scientific data
|July 27, 2024
概括
这项研究介绍了Art_GenEvalGPT,这是人工智能生成的艺术对话的新数据集. 它提供了涵盖各种艺术,艺术家和情感的细微对话,证明了AI评估的高质量.
科学领域:
- 人工智能的人工智能
- 计算语言学 计算语言学
- 艺术史 艺术史 艺术史
背景情况:
- 现有的数据集缺乏细微的艺术对话.
- 需要多样化,富有情感的AI生成对话数据.
研究的目的:
- 介绍Art_GenEvalGPT,这是一个新的合成对话数据集.
- 促进精细的AI驱动的艺术讨论和评估.
- 评估AI处理艺术的主观和情感方面的能力.
主要方法:
- 利用GenEvalGPT平台进行对话生成和评估.
- 创建了13870个合成对话,涵盖799件艺术品,378位艺术家和26种艺术风格.
- 员工对质量保证进行自动和手动评估.
主要成果:
- 通过严格的评估来证明综合对话的高质量.
- 为客观艺术属性恢复提出了有效的词汇和语义指标.
- 在使用LLM自我评估检测情绪和主观性方面取得了92%的准确性.
结论:
- Art_GenEvalGPT为基于人工智能的艺术分析提供了宝贵的资源.
- 该数据集支持在艺术领域微妙的对话性AI开发.
- 先进的指标显示,对在艺术背景下评估主观AI反应有前途.
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