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This paper proposes a system capable of recognizing a speaker's utterance-level emotion through multimodal cues in a video. The system seamlessly integrates multiple AI models to first extract and pre-process multimodal information from the raw video input. Next, an end-to-end MER model sequentially predicts the speaker's emotions at the utterance level. Additionally, users can interactively demonstrate the system through the implemented interface.