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Speech emotion recognition combining linguistic content and audio signals in the dialog is a challenging task. Nevertheless, previous approaches have failed to explore emotion cues in contextual interactions and ignored the long-range dependencies between elements from different modalities. To tackle the above issues, this letter proposes a multimodal speech emotion recognition method using audio and text data. We first present a contextual transformer module to introduce contextual information via embedding the previous utterances between interlocutors, which enhances the emotion representation of the current utterance. Then, the proposed cross-modal transformer module focuses on the interactions between text and audio modalities, adaptively promoting the fusion from one modality to another. Furthermore, we construct associative topological relation over mini-batch and learn the association between …