We propose Drax, a non-autoregressive ASR model using discrete flow matching that includes an audio-conditioned intermediate distribution to better match inference dynamics.
Drax achieves accuracy comparable to state-of-the-art autoregressive models while offering better control over the accuracy-efficiency trade-off point.