FireRedASR2 AED-L

FireRedASR2-AED is the attention-based encoder-decoder member of FireRedASR2, the successor to FireRedTeam's open-source industrial-grade FireRedASR speech-recognition family, released as part of the FireRedASR2S all-in-one ASR system. It pairs a Conformer encoder with a Transformer decoder at 1.1B parameters -- architecturally byte-identical to the original FireRedASR-AED-L -- retrained on a larger token vocabulary. The FireRedASR2S technical report (arXiv:2603.10420, Table 2) reports 3.05% average Character Error Rate across four public Mandarin benchmarks (aishell1 at 0.57%), 11.67% average CER across 19 public Chinese dialect/accent benchmarks, and 1.17% CER on a singing-lyrics benchmark, outperforming Doubao-ASR and matching Qwen3-ASR on the paper's own comparison table. It is bilingual (Mandarin Chinese and English, including code-switching). This OpenASR repo repackages the weights as .oasr packs that run natively in the OpenASR runtime -- no Python at inference time, all decoding local. The q4_k build is the recommended default for everyday use; q8_0 trades some size for closer fp16 fidelity and fp16 is for maximum fidelity or verification. Note: FireRedTeam also publishes a larger FireRedASR2-LLM (Encoder-Adapter-LLM, 2.89%/11.55% avg CER) variant that this repo does not distribute -- the numbers above are for this AED checkpoint only, and should not be conflated with the original (v1) FireRedASR-AED-L's 3.18%/0.55% figures, which come from a different training run and benchmark protocol.