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eess.AS2024★ 1 cited
SALMONN-omni: A Codec-free LLM for Full-duplex Speech Understanding and Generation
Wenyi Yu, Siyin Wang, Xiaoyu Yang +7
Full-duplex multimodal large language models (LLMs) provide a unified framework for addressing diverse speech understanding and generation tasks, enabling more natural and seamless…
eess.AS2024★ 1 cited
A unified multichannel far-field speech recognition system: combining neural beamforming with attention based end-to-end model
Dongdi Zhao, Jianbo Ma, Lu Lu +6
Far-field speech recognition is a challenging task that conventionally uses signal processing beamforming to attack noise and interference problem. But the performance has been fou…
eess.AS2023★ 5 cited
Fine-grained Audio-Visual Joint Representations for Multimodal Large Language Models
Guangzhi Sun, Wenyi Yu, Changli Tang +6
Audio-visual large language models (LLM) have drawn significant attention, yet the fine-grained combination of both input streams is rather under-explored, which is challenging but…