# FireRedASR: Open-Source Industrial-Grade Mandarin Speech Recognition Models from Encoder-Decoder to LLM Integration

arXiv: https://arxiv.org/abs/2501.14350 · HTML: https://mlsanity.com/paper/2501.14350/

## Key facts

- Cited by 46 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Jan 2025.

## Built on by (most cited first, 30 of 46)

- [DiffRhythm: Blazingly Fast and Embarrassingly Simple End-to-End Full-Length Song Generation with Latent Diffusion](https://mlsanity.com/paper/2503.01183/) (2025)
- [Fun-ASR Technical Report](https://mlsanity.com/paper/2509.12508/) (2025)
- [ContextASR-Bench: A Massive Contextual Speech Recognition Benchmark](https://mlsanity.com/paper/2507.05727/) (2025)
- [DiffRhythm 2: Efficient and High Fidelity Song Generation via Block Flow Matching](https://mlsanity.com/paper/2510.22950/) (2025)
- [WenetSpeech-Chuan: A Large-Scale Sichuanese Corpus with Rich Annotation for Dialectal Speech Processing](https://mlsanity.com/paper/2509.18004/) (2025)
- [Low-Resource Domain Adaptation for Speech LLMs via Text-Only Fine-Tuning](https://mlsanity.com/paper/2506.05671/) (2025)
- [Cross-Modal Knowledge Distillation for Speech Large Language Models](https://mlsanity.com/paper/2509.14930/) (2025)
- [MNV-17: A High-Quality Performative Mandarin Dataset for Nonverbal Vocalization Recognition in Speech](https://mlsanity.com/paper/2509.18196/) (2025)
- [Uni-ASR: Unified LLM-Based Architecture for Non-Streaming and Streaming Automatic Speech Recognition](https://mlsanity.com/paper/2603.11123/) (2026)
- [YingMusic-Singer: Zero-shot Singing Voice Synthesis and Editing with Annotation-free Melody Guidance](https://mlsanity.com/paper/2512.04779/) (2025)
- [Logics-Parsing-Omni Technical Report](https://mlsanity.com/paper/2603.09677/) (2026)
- [Audio Interaction Model](https://mlsanity.com/paper/2606.05121/) (2026)
- [Steer-MoE: Efficient Audio-Language Alignment with a Mixture-of-Experts Steering Module](https://mlsanity.com/paper/2510.13558/) (2025)
- [YingMusic-SVC: Real-World Robust Zero-Shot Singing Voice Conversion with Flow-GRPO and Singing-Specific Inductive Biases](https://mlsanity.com/paper/2512.04793/) (2025)
- [DiaMoE-TTS: A Unified IPA-Based Dialect TTS Framework with Mixture-of-Experts and Parameter-Efficient Zero-Shot Adaptation](https://mlsanity.com/paper/2509.22727/) (2025)
- [Unifying Speech Recognition, Synthesis and Conversion with Autoregressive Transformers](https://mlsanity.com/paper/2601.10770/) (2026)
- [SonicBench: Dissecting the Physical Perception Bottleneck in Large Audio Language Models](https://mlsanity.com/paper/2601.11039/) (2026)
- [Speech LLMs are Contextual Reasoning Transcribers](https://mlsanity.com/paper/2604.00610/) (2026)
- [Towards Human-Like Interactive Speech Recognition With Agentic Correction and Semantic Evaluation](https://mlsanity.com/paper/2605.29430/) (2026)
- [A Synergistic Framework of Nonlinear Acoustic Computing and Reinforcement Learning for Real-World Human-Robot Interaction](https://mlsanity.com/paper/2505.01998/) (2025)
- [Triple X: A LLM-Based Multilingual Speech Recognition System for the INTERSPEECH2025 MLC-SLM Challenge](https://mlsanity.com/paper/2507.17288/) (2025)
- [PAC: Pronunciation-Aware Contextualized Large Language Model-based Automatic Speech Recognition](https://mlsanity.com/paper/2509.12647/) (2025)
- [WEST: LLM based Speech Toolkit for Speech Understanding, Generation, and Interaction](https://mlsanity.com/paper/2509.19902/) (2025)
- [WESR: Scaling and Evaluating Word-level Event-Speech Recognition](https://mlsanity.com/paper/2601.04508/) (2026)
- [Towards Comprehensive Semantic Speech Embeddings for Chinese Dialects](https://mlsanity.com/paper/2601.07274/) (2026)
- [Zipper-LoRA: Dynamic Parameter Decoupling for Speech-LLM based Multilingual Speech Recognition](https://mlsanity.com/paper/2603.17558/) (2026)
- [Rethinking Entropy Allocation in LLM-based ASR: Understanding the Dynamics between Speech Encoders and LLMs](https://mlsanity.com/paper/2604.08003/) (2026)
- [Interactive ASR: Towards Human-Like Interaction and Semantic Coherence Evaluation for Agentic Speech Recognition](https://mlsanity.com/paper/2604.09121/) (2026)
- [NIM4-ASR: Towards Efficient, Robust, and Customizable Real-Time LLM-Based ASR](https://mlsanity.com/paper/2604.18105/) (2026)
- [Dolphin-CN-Dialect: Where Chinese Dialects Matter](https://mlsanity.com/paper/2605.08961/) (2026)

## Abstract (arXiv)

We present FireRedASR, a family of large-scale automatic speech recognition (ASR) models for Mandarin, designed to meet diverse requirements in superior performance and optimal efficiency across various applications. FireRedASR comprises two variants: FireRedASR-LLM: Designed to achieve state-of-the-art (SOTA) performance and to enable seamless end-to-end speech interaction. It adopts an Encoder-Adapter-LLM framework leveraging large language model (LLM) capabilities. On public Mandarin benchmarks, FireRedASR-LLM (8.3B parameters) achieves an average Character Error Rate (CER) of 3.05%, surpassing the latest SOTA of 3.33% with an 8.4% relative CER reduction (CERR). It demonstrates superior generalization capability over industrial-grade baselines, achieving 24%-40% CERR in multi-source Mandarin ASR scenarios such as video, live, and intelligent assistant. FireRedASR-AED: Designed to balance high performance and computational efficiency and to serve as an effective speech representation module in LLM-based speech models. It utilizes an Attention-based Encoder-Decoder (AED) architecture. On public Mandarin benchmarks, FireRedASR-AED (1.1B parameters) achieves an average CER of 3.18%, slightly worse than FireRedASR-LLM but still outperforming the latest SOTA model with over 12B parameters. It offers a more compact size, making it suitable for resource-constrained applications. Moreover, both models exhibit competitive results on Chinese dialects and English speech benchmarks and excel in singing lyrics recognition. To advance research in speech processing, we release our models and inference code at https://github.com/FireRedTeam/FireRedASR.