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On March 11th, the Tongyi Lab team announced the open-sourcing of the R1-Omni model, marking a significant advancement in multimodal model development. This model integrates reinforcement learning with verifiable reward (RLVR) methods, focusing on improving reasoning capabilities and generalization performance in multimodal emotion recognition tasks. R1-Omni's training is divided into two stages. In the cold-start phase, the team fine-tuned the model using a combined dataset containing 580 video clips sourced from Explainable Multimodal Emotion...

The 2nd MER24 Challenge focused on the application of AI in emotional recognition within real human-computer interaction scenarios, attracting renowned international scholars. The voice technology team from Soul App excelled in the highly challenging Semi track, winning first place. Their success stemmed from innovations in multimodal data understanding, emotional recognition algorithms, model optimization, and efficient collaboration. To tackle ....