# FireRedASR2S: A State-of-the-Art Industrial-Grade All-in-One Automatic Speech Recognition System

arXiv: https://arxiv.org/abs/2603.10420 · HTML: https://mlsanity.com/paper/2603.10420/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Mar 2026.

## Built on by (most cited first, 16 of 16)

- [Cosmos 3: Omnimodal World Models for Physical AI](https://mlsanity.com/paper/2606.02800/) (2026)
- [MSAVBench: Towards Comprehensive and Reliable Evaluation of Multi-Shot Audio-Video Generation](https://mlsanity.com/paper/2605.20183/) (2026)
- [Mega-ASR: Towards In-the-wild^2 Speech Recognition via Scaling up Real-world Acoustic Simulation](https://mlsanity.com/paper/2605.19833/) (2026)
- [Multimodal Duplex Interaction Agent](https://mlsanity.com/paper/2609.08977/) (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)
- [Language-Specialized Multi-Teacher On-Policy Distillation for Multilingual LLM-Based ASR](https://mlsanity.com/paper/2608.03610/) (2026)
- [StepAudio 3 Music Technical Report](https://mlsanity.com/paper/2609.16034/) (2026)
- [DialectS2S: End-to-End Speech Dialogue Modeling for Low-Resource Chinese Dialects](https://mlsanity.com/paper/2608.08067/) (2026)
- [Dual-Form ASR: Semantics-Aware Inverse Text Normalization for Chinese Speech Recognition](https://mlsanity.com/paper/2609.02901/) (2026)
- [HearInContext: A Benchmark for Implicit Context in Speech Recognition](https://mlsanity.com/paper/2609.18680/) (2026)
- [Alignment-Path Distillation from Non-streaming ASR-LLMs for Streaming Speech Recognition](https://mlsanity.com/paper/2609.20121/) (2026)
- [A Native-Reference Phone-Class Geometry for Second-Language Pronunciation Analysis](https://mlsanity.com/paper/2609.30075/) (2026)
- [AVIO: Learning to Add and Remove Sounding Objects in Audiovisual Scenes](https://mlsanity.com/paper/2609.36503/) (2026)
- [ASSET: Adaptive Speech Segmentation via Reinforcement Learning](https://mlsanity.com/paper/2610.14309/) (2026)
- [ScreenASR-Bench: A Tiered Benchmark for Speech Recognition with Visual Context](https://mlsanity.com/paper/2610.16260/) (2026)

## Abstract (arXiv)

We present FireRedASR2S, a state-of-the-art industrial-grade all-in-one automatic speech recognition (ASR) system. It integrates four modules in a unified pipeline: ASR, Voice Activity Detection (VAD), Spoken Language Identification (LID), and Punctuation Prediction (Punc). All modules achieve SOTA performance on the evaluated benchmarks: FireRedASR2: An ASR module with two variants, FireRedASR2-LLM (8B+ parameters) and FireRedASR2-AED (1B+ parameters), supporting speech and singing transcription for Mandarin, Chinese dialects and accents, English, and code-switching. Compared to FireRedASR, FireRedASR2 delivers improved recognition accuracy and broader dialect and accent coverage. FireRedASR2-LLM achieves 2.89% average CER on 4 public Mandarin benchmarks and 11.55% on 19 public Chinese dialects and accents benchmarks, outperforming competitive baselines including Doubao-ASR, Qwen3-ASR, and Fun-ASR. FireRedVAD: An ultra-lightweight module (0.6M parameters) based on the Deep Feedforward Sequential Memory Network (DFSMN), supporting streaming VAD, non-streaming VAD, and multi-label VAD (mVAD). On the FLEURS-VAD-102 benchmark, it achieves 97.57% frame-level F1 and 99.60% AUC-ROC, outperforming Silero-VAD, TEN-VAD, FunASR-VAD, and WebRTC-VAD. FireRedLID: An Encoder-Decoder LID module supporting 100+ languages and 20+ Chinese dialects and accents. On FLEURS (82 languages), it achieves 97.18% utterance-level accuracy, outperforming Whisper and SpeechBrain. FireRedPunc: A BERT-style punctuation prediction module for Chinese and English. On multi-domain benchmarks, it achieves 78.90% average F1, outperforming FunASR-Punc (62.77%). To advance research in speech processing, we release model weights and code at https://github.com/FireRedTeam/FireRedASR2S.