OpenSTBench: Beyond Semantic Evaluation for Speech Translation 文章

ArXiv CS.AI2026-06-01NEWSen作者: Yanjie An, Yuxiang Zhao, Yichi Zhang, Qixi Zheng, Yujie Tu, Keqi Deng, Kai Yu, Xie Chen

摘要

arXiv:2605.30792v1 Announce Type: cross Abstract: Speech translation systems increasingly span speech-to-text translation (S2TT), speech-to-speech translation (S2ST), offline translation, and streaming generation, producing outputs that differ in modality, speech realization, and timing behavior. Existing evaluation practices assess important aspects such as translation quality, speech quality, and temporal quality, but these aspects are often evaluated under separate protocols, making it difficult to compare heterogeneous systems comprehensively. To address this gap, we present OpenSTBench, a unified multidimensional evaluation framework that organizes heterogeneous speech translation outputs into a shared evaluation format. OpenSTBench supports both S2TT and S2ST systems in offline and streaming settings, and jointly evaluates translation quality, speech quality, speaker preservation, emotion and paralinguistic fidelity, temporal consistency, and latency.

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