An integrated framework for emotion and sentiment analysis in Tamil and Malayalam visual content.
Sentiment analysis in low-resource languages such as Tamil and Malayalam presents significant challenges due to the scarcity of linguistic resources and the intricacy of cultural contexts. To address these challenges, we propose the Integrated Multimodal Sentiment Dynamics (IMSD) Framework, an innov...
| Publicado en: | Language Resources & Evaluation Vol. 59; no. 3; pp. 2103 - 2142 |
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| Autores principales: | , |
| Formato: | Artículo |
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Springer Nature
Sep2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=186909063&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 186909063 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Sep2025 vid: 59 iid: 3 pid: 237 pub: Springer Nature artinfo: ui: 186909063 10.1007/s10579-024-09804-1 ppf: 2103 ppct: 39 formats: fmt: – @attributes: type: T – @attributes: type: P size: 2.4MB tig: atl: An integrated framework for emotion and sentiment analysis in Tamil and Malayalam visual content. aug: au: Prakash, V. Jothi Vijay, S. Arul Antran affil: https://ror.org/01qhf1r47 Karpagam College of Engineering, Coimbatore, Tamil Nadu, India su: Sentiment analysis Low-resource languages Tamil (Indic people) Multimodal user interfaces Emotion recognition Feature extraction Malay language Cultural adaptation sug: subj: Sentiment analysis Low-resource languages Tamil (Indic people) Multimodal user interfaces Emotion recognition Feature extraction Malay language Cultural adaptation keyword: Cultural contextualization Deep learning Multimodal sentiment analysis Natural language processing ab: Sentiment analysis in low-resource languages such as Tamil and Malayalam presents significant challenges due to the scarcity of linguistic resources and the intricacy of cultural contexts. To address these challenges, we propose the Integrated Multimodal Sentiment Dynamics (IMSD) Framework, an innovative solution specifically tailored for analyzing Tamil and Malayalam visual content. The framework is novel in its integration of visual, audio, and textual modalities, employing advanced feature extraction technologies such as I3D and mBERT for innovative feature fusion and a cultural adaptation layer to ensure sensitivity and appropriateness to regional nuances. Utilizing the DravidianMultiModality dataset, consisting of 1340 multimedia samples, IMSD significantly outperforms traditional models like Naïve Bayes, SVM, and LSTM, achieving impressive metrics with an accuracy of 86.3%, precision of 87.5%, and recall of 86.0%. Notably, the framework exhibits exceptional performance in cross-linguistic adaptability, demonstrated through its successful application to the Bengali MemoSen dataset, enhancing its potential applicability across diverse linguistic contexts. These findings underline IMSD's capability to set new benchmarks in multimodal sentiment analysis for under-resourced languages, highlighting its adaptability and the critical role of cultural understanding in sentiment analysis. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2025. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2025 holdings: @attributes: islocal: N |
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