LPM
Local Prior Matching
**Local Prior Matching** is a semi-supervised objective for speech recognition that distills knowledge from a strong prior (e.g. a language model) to provide learning signal to a discriminative model trained on unlabeled speech. The LPM objective minimizes the cross entropy between the local prior and the model distribution, and is minimized when $q\_{y\mid{x}} = \bar{p}\_{y\mid{x}}$. Intuitively, LPM encourages the ASR model to assign posterior probabilities proportional to the linguistic probabilities of the proposed hypotheses.
Semi-Supervised Speech Recognition via Local Prior Matching
https://paperswithcode.com/paper/semi-supervised-speech-recognition-via-local
Semi-Supervised Speech Recognition via Local Prior Matching