Mega ASR takes on dirty real-world audio
Researchers just dropped Mega ASR, a lightweight speech recognition model built specifically for noisy, distorted real-world audio. Trained on 2.6 million challenging samples covering reverberation, clipping, and severe background interference, it cuts error rates by over 30% against leading baselines. The entire model sits under 5GB, meaning developers can easily run and fine-tune it locally on consumer GPUs.