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Found 4 papers, 0 papers with code
Progressive unsupervised domain adaptation for ASR using ensemble models and multi-stage training
A previous study has shown the effectiveness of using ensemble teacher models in T/S training for unsupervised domain adaptation (UDA) but its performance still lags behind compared to the model trained on in-domain data.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
MUST: A Multilingual Student-Teacher Learning approach for low-resource speech recognition
However, a limitation of KD training is that the student model classes must be a proper or improper subset of the teacher model classes.
Towards domain generalisation in ASR with elitist sampling and ensemble knowledge distillation
Knowledge distillation has widely been used for model compression and domain adaptation for speech applications.
Unsupervised data selection for Speech Recognition with contrastive loss ratios
By using the submodular function, a training set for automatic speech recognition matching the target data set is selected.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
