Abstract
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 this https URL.
Abstract (translated)
我们介绍FireRedASR2S，这是一个最先进的工业级一体化自动语音识别（ASR）系统。它在一个统一的流水线中集成了四个模块：ASR、语音活动检测（VAD）、口语语言识别（LID）和标点预测（Punc）。所有模块在评估基准上均达到了最先进水平（SOTA）： - FireRedASR2: 包含两个变体，FireRedASR2-LLM（8B+参数）和支持语音和演唱转写的FireRedASR2-AED（1B+参数），支持普通话、中国方言及口音、英语以及代码切换。与前代相比，FireRedASR2在识别准确性和更广泛的方言及口音覆盖范围方面都有所改进。FireRedASR2-LLM在中国语料库的四个公共基准上平均CER为2.89%，在19个公共中国方言和口音基准上的平均CER为11.55%，优于包括Doubao-ASR、Qwen3-ASR和Fun-ASR在内的竞争基线。 - FireRedVAD：一个基于深度前馈序列记忆网络（DFSMN）的超轻量级模块，支持流式语音活动检测（streaming VAD）、非流式语音活动检测（non-streaming VAD）以及多标签语音活动检测（mVAD）。在FLEURS-VAD-102基准上，它实现了97.57%的帧级F1和99.60%AUC-ROC，优于Silero-VAD、TEN-VAD、FunASR-VAD及WebRTC-VAD。 - FireRedLID：一个支持超过100种语言和20多种中国方言及口音的编码器解码器模块。在FLEURS（82种语言）上，它实现了97.18%的句子级准确率，优于Whisper和SpeechBrain。 - FireRedPunc：针对中文和英文的BERT风格标点预测模块，在多领域基准上平均F1为78.90%，优于FunASR-Punc（62.77%）。 为了推进语音处理领域的研究，我们将在[此链接](https://this-url.com)发布模型权重及代码。
URL
https://arxiv.org/abs/2603.10420
