4 papers · 1 filter
Evaluating and Preserving Lexical Stress in English-to-Chinese Speech-to-Speech Translation
Yuchen Song, Xi Chen, Mingze Li +1
Speech-to-speech translation (S2ST) systems have achieved impressive progress in semantic accuracy and speech naturalness. However, the cross-lingual transfer of lexical stress, a…
StressTransfer: Stress-Aware Speech-to-Speech Translation with Emphasis Preservation
Xi Chen, Yuchen Song, Satoshi Nakamura
We propose a stress-aware speech-to-speech translation (S2ST) system that preserves word-level emphasis by leveraging LLMs for cross-lingual emphasis conversion. Our method transla…
SASST: Leveraging Syntax-Aware Chunking and LLMs for Simultaneous Speech Translation
Zeyu Yang, Lai Wei, Roman Koshkin +2
This work proposes a grammar-based chunking strategy that segments input streams into semantically complete units by parsing dependency relations (e.g., noun phrase boundaries, ver…
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…