CoVoST2 en-zh

CoVoST 2 English-to-Chinese subset is part of the large-scale multilingual speech translation corpus derived from Common Voice. This subset focuses specifically on English to Chinese speech translation tasks within the broader CoVoST 2 dataset.

Qwen2.5-Omni-7B from Alibaba Cloud / Qwen Team currently leads the CoVoST2 en-zh leaderboard with a score of 0.414 across 1 evaluated AI models.

Paper

Alibaba Cloud / Qwen TeamQwen2.5-Omni-7B leads with 0.4%.

Progress Over Time

Interactive timeline showing model performance evolution on CoVoST2 en-zh

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CoVoST2 en-zh Leaderboard

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Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
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FAQ

Common questions about CoVoST2 en-zh.

What is the CoVoST2 en-zh benchmark?

CoVoST 2 English-to-Chinese subset is part of the large-scale multilingual speech translation corpus derived from Common Voice. This subset focuses specifically on English to Chinese speech translation tasks within the broader CoVoST 2 dataset.

What is the CoVoST2 en-zh leaderboard?

The CoVoST2 en-zh leaderboard ranks 1 AI models based on their performance on this benchmark. Currently, Qwen2.5-Omni-7B by Alibaba Cloud / Qwen Team leads with a score of 0.414. The average score across all models is 0.414.

What is the highest CoVoST2 en-zh score?

The highest CoVoST2 en-zh score is 0.414, achieved by Qwen2.5-Omni-7B from Alibaba Cloud / Qwen Team.

How many models are evaluated on CoVoST2 en-zh?

1 models have been evaluated on the CoVoST2 en-zh benchmark, with 0 verified results and 1 self-reported results.

Where can I find the CoVoST2 en-zh paper?

The CoVoST2 en-zh paper is available at https://arxiv.org/abs/2007.10310. The paper details the methodology, dataset construction, and evaluation criteria.

What categories does CoVoST2 en-zh cover?

CoVoST2 en-zh is categorized under audio, language, and speech to text. The benchmark evaluates audio models with multilingual support.

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