Deep Contextualized Acoustic Representations For Semi-Supervised Speech Recognition
ICASSP, pp. 6429-6433, 2019.
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 a temporal slice of filterbank features from past and future context frames. The resulting deep contextualized acoustic representations (DeCoAR) are ...More
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