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
About this benchmark

What CoVoST2 en-zh measures

CoVoST2 en-zh is a audio benchmark that evaluates large language models on language, speech to text, and audio tasks. LLM Stats tracks 1 model on this benchmark, with a maximum possible score of 100. Current average across reported models is 0.4, with the leader reaching 0.4.

Compare leaders on the best AI for language, best AI for speech to text and best AI for audio leaderboards.

Publication

Paper
CoVoST 2 and Massively Multilingual Speech-to-Text Translation
Authors
Changhan Wang, Anne Wu, Juan Pino
Published

Abstract

Speech translation has recently become an increasingly popular topic of research, partly due to the development of benchmark datasets. Nevertheless, current datasets cover a limited number of languages. With the aim to foster research in massive multilingual speech translation and speech translation for low resource language pairs, we release CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. This represents the largest open dataset available to date from total volume and language coverage perspective. Data sanity checks provide evidence about the quality of the data, which is released under CC0 license. We also provide extensive speech recognition, bilingual and multilingual machine translation and speech translation baselines with open-source implementation.

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

Progress Over Time

Interactive timeline showing model performance evolution on CoVoST2 en-zh

State-of-the-art frontier
Open
Proprietary

CoVoST2 en-zh Leaderboard

1 models
ContextCostLicense
1
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
7B
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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 language, speech to text, and audio. The benchmark evaluates audio models with multilingual support.

What is the best open-source model on CoVoST2 en-zh?

Qwen2.5-Omni-7B by Alibaba Cloud / Qwen Team is the top-ranked open-source model on CoVoST2 en-zh, with a score of 0.414 (rank #1).

How recent are the CoVoST2 en-zh leaderboard results?

The CoVoST2 en-zh leaderboard was last updated in June 2026 and currently includes 1 evaluated models.

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