SALMONN integrates speech and audio encoders with a text-based LLM to process general audio inputs, achieve competitive results on trained tasks, and exhibit emergent cross-modal abilities.
arXiv:2307.03917 , year=
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Qwen2.5-Omni presents a multimodal model with block-wise encoders, TMRoPE position embeddings, and a Thinker-Talker architecture that enables simultaneous text and streaming speech generation while matching text performance on reasoning benchmarks.
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SALMONN: Towards Generic Hearing Abilities for Large Language Models
SALMONN integrates speech and audio encoders with a text-based LLM to process general audio inputs, achieve competitive results on trained tasks, and exhibit emergent cross-modal abilities.
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Qwen2.5-Omni Technical Report
Qwen2.5-Omni presents a multimodal model with block-wise encoders, TMRoPE position embeddings, and a Thinker-Talker architecture that enables simultaneous text and streaming speech generation while matching text performance on reasoning benchmarks.