FunASR and Fun-ASR

These are competing projects that both provide end-to-end ASR systems with similar core functionality, though FunASR from ModelScope appears to be the more established toolkit while Fun-ASR from FunAudioLLM integrates LLM capabilities for potentially richer speech understanding.

FunASR
62
Established
Fun-ASR
50
Established
Maintenance 16/25
Adoption 10/25
Maturity 16/25
Community 20/25
Maintenance 10/25
Adoption 10/25
Maturity 13/25
Community 17/25
Stars: 15,283
Forks: 1,605
Downloads:
Commits (30d): 2
Language: Python
License: MIT
Stars: 946
Forks: 81
Downloads:
Commits (30d): 0
Language: Python
License: Apache-2.0
No Package No Dependents
No Package No Dependents

About FunASR

modelscope/FunASR

A Fundamental End-to-End Speech Recognition Toolkit and Open Source SOTA Pretrained Models, Supporting Speech Recognition, Voice Activity Detection, Text Post-processing etc.

Built on non-autoregressive architectures like Paraformer, FunASR combines ASR with complementary tasks—VAD, punctuation restoration, speaker diarization, and emotion recognition—within a unified framework. The toolkit integrates with ModelScope and Hugging Face for model distribution, and provides production-ready runtime services with optimized CPU/GPU inference pipelines supporting both offline batch processing and low-latency streaming transcription across 31+ languages.

About Fun-ASR

FunAudioLLM/Fun-ASR

Fun-ASR is an end-to-end speech recognition large model launched by Tongyi Lab.

Supports 31 languages with specialized optimization for dialects and accents (7 Chinese dialects, 26 regional accents), enabling low-latency real-time transcription via an end-to-end architecture trained on tens of millions of hours of speech data. Features include VAD integration, punctuation restoration, hotword customization, and robust performance in far-field/high-noise scenarios (93% accuracy). Integrates with ModelScope and Hugging Face ecosystems through the `funasr` toolkit, supporting inference via `AutoModel` or direct model loading with configurable language, ITN (inverse text normalization), and batch processing.

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