We evaluate the noise robustness of the Distil-Whisper models, the original Whisper models, and
eight other LibriSpeech-trained models by measuring the WER on the LibriSpeech test-clean dataset
with increasing amounts of noise applied to the input audio. The LibriSpeech dataset is an ideal
choice of dataset since it has a high signal-to-noise ratio (SNR), and thus enablers evaluation over
a large range of SNRs as the amount of noise is increased. We add either white noise or pub noise
from the Audio Degradation Toolbox (Mauch & Ewert, 2013). The pub noise simulates a naturally
noisy environment, with ambient sounds and indistinguishable conversations characteristic of a busy
restaurant or pub. The level of additive noise is determined based on the signal power of individual
instances, and corresponds to a specified SNR.
DISTIL-WHISPER