Stream-Omni: Simultaneous Multimodal Interactions with Large Language-Vision-Speech Model

👁 arXiv
👁 arXiv
👁 model
👁 data
👁 Badge

Shaolei Zhang, Shoutao Guo, Qingkai Fang, Yan Zhou, Yang Feng*

The introduction and usage of Stream-Omni refer to https://github.com/ictnlp/Stream-Omni.

Stream-Omni is an end-to-end language-vision-speech chatbot that simultaneously supports interaction across various modality combinations, with the following features💡:

• Omni Interaction: Support any multimodal inputs including text, vision, and speech, and generate both text and speech responses.
• Seamless "see-while-hear" Experience: Simultaneously output intermediate textual results (e.g., ASR transcriptions and model responses) during speech interactions, like the advanced voice service of GPT-4o.
• Efficient Training: Require only a small amount of omni-modal data for training.

👁 stream-omni

🖥 Demo

Stream-Omni can produce intermediate textual results (ASR transcription and text response) during speech interaction, offering users a seamless "see-while-hear" experience.