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Deep Contextualized Acoustic Representations For Semi-Supervised Speech Recognition
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Deep Contextualized Acoustic Representations For Semi-Supervised Speech Recognition
We propose a novel approach to semi-supervised automatic speech recognition (ASR). We first exploit a large amount of unlabeled audio data via representation learning, where we reconstruct an unseen temporal slice of filterbank features from past and futu
We propose a novel approach to semi-supervised automatic speech recognition (ASR). We first exploit a large amount of unlabeled audio data via representation learning, where we reconstruct an unseen temporal slice of filterbank features from past and futu
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