An overview of Multimodal Sentiment Analysis research: Opportunities and Difficulties

Mohammad Aman Ullah, Md. Monirul Islam, N. Azman, Z. M. Zaki
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引用次数: 12

Abstract

The scatter form of multimedia data such as text, image, audio, and video posted regularly in the social media may contain useful information for the organizations. But, this information should be derived with the use of some form of analysis known as Multimodal Sentiment Analysis (MSA). But, there is a lack of proper analytic tools for such analysis. This paper presents a thorough overview of more than fifty most recent MSA research articles to find the gaps in terms of tasks, approaches theories and applications used till date. There seems to be no single approach, theory, and tool which can support MSA. The study showed that each and every mode presents different difficulties which have not bee n fully solved yet, such as feature points of a face, voice clarity in audio, video summarization and so on, and are great research opportunities for the future researchers. Also, this research recommends a list of existing and upcoming difficulties and opportunities of MSA research.
多模态情感分析研究综述:机遇与困难
在社交媒体上定期发布的文本、图像、音频和视频等多媒体数据的散点形式可能包含对组织有用的信息。但是,这些信息应该通过使用某种称为多模态情感分析(MSA)的分析形式来获得。但是,缺乏适当的分析工具来进行这种分析。本文对50多篇最新的MSA研究文章进行了全面的概述,以找到迄今为止在任务、方法、理论和应用方面的差距。似乎没有单一的方法、理论和工具可以支持MSA。研究表明,每种模式都存在不同的尚未完全解决的难点,如人脸特征点、音频语音清晰度、视频摘要等,这对未来的研究人员来说是很好的研究机会。此外,本研究还提出了MSA研究的现有和未来的困难和机遇。
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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