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Found 5 papers, 2 papers with code
REBORN: Reinforcement-Learned Boundary Segmentation with Iterative Training for Unsupervised ASR
REBORN alternates between (1) training a segmentation model that predicts the boundaries of the segmental structures in speech signals and (2) training the phoneme prediction model, whose input is the speech feature segmented by the segmentation model, to predict a phoneme transcription.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Improving Cascaded Unsupervised Speech Translation with Denoising Back-translation
We use fully unpaired data to train our unsupervised systems and evaluate our results on CoVoST 2 and CVSS.
Introducing Semantics into Speech Encoders
Recent studies find existing self-supervised speech encoders contain primarily acoustic rather than semantic information.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+10
Improving generalizability of distilled self-supervised speech processing models under distorted settings
Self-supervised learned (SSL) speech pre-trained models perform well across various speech processing tasks.
Mandarin-English Code-switching Speech Recognition with Self-supervised Speech Representation Models
Code-switching (CS) is common in daily conversations where more than one language is used within a sentence.
