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IEEE/ICACT20240342 Slide.07        [Big Slide]	Oral Presentation
	Let¡®s take a closer look at how multimodal feature extraction module works. We take three token-level unimodal features as input and gain their utterance-level features represent, and concatenate these six features to obtain the fused features. Then we use the attention mechanism to obtain attention score and updated multimodal feature $X_{m}^{\prime}$ Eventually, we split the interactive features into two sets and passing through several linear layers, we obtain the multimodal features representation.

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