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cs.CL2026
Bridging What the Model Thinks and How It Speaks: Expressive Speech Generation via Self-Aware Intent-Realization Alignment
Kuang Wang, Lai Wei, Ping Lin +8
Speech Language Models (SLMs) exhibit strong semantic understanding, yet often fail to translate this capacity into expressive acoustic realization, producing speech with flattened…
cs.CL2024★ 1 cited
LLaST: Improved End-to-end Speech Translation System Leveraged by Large Language Models
Xi Chen, Songyang Zhang, Qibing Bai +2
We introduces LLaST, a framework for building high-performance Large Language model based Speech-to-text Translation systems. We address the limitations of end-to-end speech transl…
cs.CL2022★ 2 cited
Leveraging Pseudo-labeled Data to Improve Direct Speech-to-Speech Translation
Qianqian Dong, Fengpeng Yue, Tom Ko +3
Direct Speech-to-speech translation (S2ST) has drawn more and more attention recently. The task is very challenging due to data scarcity and complex speech-to-speech mapping. In th…