--- license: apache-2.0 language: - zh - en metrics: - wer tags: - ASR - onnx --- ## Introduction This is a xlarge [zipformer](https://arxiv.org/pdf/2310.11230) model developed by Xiaomi AI Lab Next-gen-Kaldi team. The model was trained on around 20,0000 hours of open-sourced Chinese and English datasets. The number of parameters is around 300M. The performance on some popular test sets (CER for Chinese, WER for English). > This model was trained with ctc head only. | Head | aishell test 1 / 2 | wenetspeech test-net/meetting | Common Voice zh | kespeech test | librispeech test-clean / other | gigaspeech test | Common voice en | tedium test | | -- | -- | -- | -- | -- | -- | -- | -- | -- | | CTC | 1.61 / 2.7 | 5.35 / 6.39 | 8.26 | 5.74 | 3.51 / 7.78 | 14.53 | 28.57 | 15.07 | Please refer to [zipformer in github](https://github.com/pkufool/zipformer) for model details. > Training set list: Librispeech, Gigaspeech, Commonvoice-2022(zh + en), Libriheavy, Emilia (zh+en), AIshell 2, Wenetspeech, Wenetspeech4tts, Kespeech, AIshell, aidatatang, aishell4, alimeeting, magicdata, primewords, stcmds, thchs30. ## Documentation Please refer to [https://pkufool.github.io/zipformer/en/models/](https://pkufool.github.io/zipformer/en/models/) ## Citation ``` @inproceedings{yao2024zipformer, title={Zipformer: A faster and better encoder for automatic speech recognition}, author={Yao, Zengwei and Guo, Liyong and Yang, Xiaoyu and Kang, Wei and Kuang, Fangjun and Yang, Yifan and Jin, Zengrui and Lin, Long and Povey, Daniel}, booktitle={International Conference on Learning Representations}, volume={2024}, pages={44440--44455}, year={2024} } @inproceedings{yao2025cr, title={Cr-ctc: Consistency regularization on ctc for improved speech recognition}, author={Yao, Zengwei and Kang, Wei and Yang, Xiaoyu and Kuang, Fangjun and Guo, Liyong and Zhu, Han and Jin, Zengrui and Li, Zhaoqing and Lin, Long and Povey, Daniel}, booktitle={International Conference on Learning Representations}, volume={2025}, pages={26850--26868}, year={2025} } ```