MelHuBERT: A simplified HuBERT on Mel spectrogram. (arXiv:2211.09944v1 [cs.CL])

Self-supervised models have had great success in learning speech
representations that can generalize to various downstream tasks. HuBERT, in
particular, achieves strong performance while being relatively simple in
training compared to others. The original experimental setting is
computationally extensive, hindering the reproducibility of the models. It is
also unclear why certain design decisions are made, such as the ad-hoc loss
function, and whether these decisions have an impact on the learned
representations. We propose MelHuBERT, a simplified version of HuBERT …

arxiv simplified spectrogram