In this paper, a novel dual-modal approach merges audio and textual data for emotion classification. By combining BERT and ModifiedAlexNet models, it surpasses single-modal models on IEMOCAP dataset. The work enhances human-computer interaction and inspires further research in multi-modal emotion recognition.
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In this paper, a novel dual-modal approach merges audio and textual data for emotion classification. By combining BERT and ModifiedAlexNet models, it surpasses single-modal models on IEMOCAP dataset. The work enhances human-computer interaction and inspires further research in multi-modal emotion recognition.
malikbaqi12/A-Hybrid-Approach-to-Emotion-Classification-Using-Multimodal-Text-and-Audio-Data
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In this paper, a novel dual-modal approach merges audio and textual data for emotion classification. By combining BERT and ModifiedAlexNet models, it surpasses single-modal models on IEMOCAP dataset. The work enhances human-computer interaction and inspires further research in multi-modal emotion recognition.
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