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ARXIV:2605.30792 · SPEECH TRANSLATION EVALUATION · SUBMITTED 01 JUN · 20:23 UTC · FRESHNESS STALE
ARXIV:2605.30792SPEECH TRANSLATION EVALUATIONSUBMITTED 01 JUN · 20:23 UTCFRESHNESS STALEYanjie An · Yuxiang Zhao · Yichi Zhang · Qixi Zheng · Yujie Tu · Keqi Deng · +2 at arXiv
A unified framework and dataset for comprehensive, multidimensional evaluation of speech translation systems, enabling application-oriented comparisons.
Opportunity summary
Pain A unified framework and dataset for comprehensive, multidimensional evaluation of speech translation systems, enabling application-oriented comparisons.
Evidence 0 refs | 4 sources | 67% coverage
Blocker Evidence unverified
A unified framework and dataset for comprehensive, multidimensional evaluation of speech translation systems, enabling application-oriented comparisons. Existing evaluation practices assess important aspects such as translation quality, speech quality, and temporal quality, but these aspects…
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…
ScienceToStartup currently rates this 7.0/10 on the public viability pass. OpenSTBench supports both S2TT and S2ST systems in offline and streaming settings, and jointly evaluates translation quality, speech quality, speaker preservation, emotion and paralinguistic…
Speech Translation Evaluation moved forward this cycle; last verified June 2026. Public score 7.0/10. Implementation evidence is present through a linked repository.
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A unified framework and dataset for comprehensive, multidimensional evaluation of speech translation systems, enabling application-oriented comparisons.
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10.48550/arXiv.2605.30792A unified framework and dataset for comprehensive, multidimensional evaluation of speech translation systems, enabling application-oriented comparisons.
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. Through experiments on representative speech translation systems, we show that systems with strong translation quality can still differ substantially in speech quality, as well as in temporal quality. OpenSTBench provides a reproducible protocol for analyzing these cross-dimensional differences and supporting application-oriented comparison of speech translation systems. The code and datasets are available at https://github.com/sjtuayj/OpenSTBench.
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unverified0 refs; 4 sources; 67% coverage.
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PROBLEM
A unified framework and dataset for comprehensive, multidimensional evaluation of speech translation systems, enabling application-oriented comparisons. Existing evaluation practices assess important aspects such as translation quality, speech quality, and temporal quality, but...
METHOD
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 a...
RESULT
ScienceToStartup currently rates this 7.0/10 on the public viability pass. 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, tem...
WHY NOW
Speech Translation Evaluation moved forward this cycle; last verified June 2026. Public score 7.0/10. Implementation evidence is present through a linked repository.
{"file name": "input.pdf", "number of pages": 12, "author": "Yanjie An; Yuxiang Zhao; Yichi Zhang; Qixi Zheng; Yujie Tu; Keqi Deng; Kai Yu; Xie Chen"
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A unified framework and dataset for comprehensive, multidimensional evaluation of speech translation systems, enabling application-oriented comparisons.
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Speech Translation Evaluation
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