FireRedLID is the Spoken Language Identification (LID) module of FireRedASR2S, a state-of-the-art (SOTA), industrial-grade, all-in-one ASR system. It supports 100+ languages and 20+ Chinese dialects/accents, achieving 97.18% accuracy on the FLEURS benchmark, outperforming Whisper and SpeechBrain-LID.
This model was introduced in the paper FireRedASR2S: A State-of-the-Art Industrial-Grade All-in-One Automatic Speech Recognition System.
🔥 News
- [2026.02.12] We release FireRedASR2S (FireRedASR2-AED, FireRedVAD, FireRedLID, and FireRedPunc) with model weights and inference code.
Evaluation
FireRedLID
Metric: Utterance-level LID Accuracy (%). Higher is better.
| Testset\Model | Languages | FireRedLID | Whisper | SpeechBrain | Dolphin |
|---|---|---|---|---|---|
| FLEURS test | 82 languages | 97.18 | 79.41 | 92.91 | - |
| CommonVoice test | 74 languages | 92.07 | 80.81 | 78.75 | - |
| KeSpeech + MagicData | 20+ Chinese dialects/accents | 88.47 | - | - | 69.01 |
Sample Usage
To use this module independently, first clone the GitHub repository and install the dependencies.
Python API Usage
from fireredasr2s.fireredlid import FireRedLid, FireRedLidConfig
batch_uttid = ["hello_zh", "hello_en"]
batch_wav_path = ["assets/hello_zh.wav", "assets/hello_en.wav"]
config = FireRedLidConfig(use_gpu=True, use_half=False)
model = FireRedLid.from_pretrained("FireRedTeam/FireRedLID", config)
results = model.process(batch_uttid, batch_wav_path)
print(results)
# [{'uttid': 'hello_zh', 'lang': 'zh mandarin', 'confidence': 0.996, 'dur_s': 2.32, 'rtf': '0.0741', 'wav': 'assets/hello_zh.wav'}, {'uttid': 'hello_en', 'lang': 'en', 'confidence': 0.996, 'dur_s': 2.24, 'rtf': '0.0741', 'wav': 'assets/hello_en.wav'}]
Citation
@article{xu2026fireredasr2s,
title={FireRedASR2S: A State-of-the-Art Industrial-Grade All-in-One Automatic Speech Recognition System},
author={Xu, Kaituo and Jia, Yan and Huang, Kai and Chen, Junjie and Li, Wenpeng and Liu, Kun and Xie, Feng-Long and Tang, Xu and Hu, Yao},
journal={arXiv preprint arXiv:2603.10420},
year={2026}
}