xzf-thu/Mega-ASR

Health v2 · maintenance only

Flags: no_releases young no_license

Adoption not part of the score

1136 stars · 74 forks observed · 2026-09-03

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Mega-ASR is a foundation automatic speech recognition model trained on 2.6M samples spanning 7 atomic acoustic conditions and 54 compound real-world scenarios, using A2S-SFT and DG-WGPO reinforcement learning. The repository provides training code, model weights, and an associated dataset and benchmark for robust in-the-wild speech recognition.

Use cases

• transcribe speech in noisy real-world environments
• recognize far-field or reverberant audio
• evaluate ASR robustness across acoustic conditions
• train a robust speech recognition model
• benchmark ASR models against challenging audio
• download open ASR model weights

When to choose

• your ASR pipeline fails on noisy, far-field, or distorted real-world audio
• you need a robust open ASR foundation model with weights and training data
• you want to benchmark speech recognition under compound acoustic scenarios

When to avoid

• you need a lightweight ASR for clean studio audio
• you require a permissive license - the repo has no license
• you need streaming or low-latency on-device transcription

Facets

library · maturity active

speech-recognition machine-learning deep-learning llm-training data-generation speech-processing machine-learning artificial-intelligence python asr robust-speech-recognition acoustic-simulation foundation-model reinforcement-learning dataset model-weights audio gpu linux

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markdown · JSON · MCP: product_card(name="xzf-thu/Mega-ASR")