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This is a Quantitative Study study.

September 20, 2025

Picturized and Recited with Dialects: A Multimodal Chinese Representation Framework for Sentiment Analysis of Classical Chinese Poetry

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The proposed framework achieves a 2.51% improvement in accuracy for sentiment analysis of classical Chinese poetry.
Incorporating dialect audio features enriches the phonetic representation and enhances textual analysis.
The study utilizes multimodal contrastive representation learning to fuse audio, visual, and textual features.
Open-sourced code contributes to advancing research methodologies in sentiment analysis of classical Chinese literature.

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Implication

Research demonstrates enhanced sentiment analysis in classical Chinese poetry through dialect integration, suggesting improvements in multimodal representation methods.

Cite This Study

Du et al. (2025) studied this question.

synapsesocial.com/papers/68d469d631b076d99fa670bb https://doi.org/10.24963/ijcai.2025/310

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Implication

Research demonstrates enhanced sentiment analysis in classical Chinese poetry through dialect integration, suggesting improvements in multimodal representation methods.

Picturized and Recited with Dialects: A Multimodal Chinese Representation Framework for Sentiment Analysis of Classical Chinese Poetry

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Implication

Cite This Study

Picturized and Recited with Dialects: A Multimodal Chinese Representation Framework for Sentiment Analysis of Classical Chinese Poetry

Key Points

Discussion

Implication

Cite This Study

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