vq-wav2vec: Self-Supervised Learning of Discrete Speech Representations

ICLR 2020 Alexei BaevskiSteffen SchneiderMichael Auli

We propose vq-wav2vec to learn discrete representations of audio segments through a wav2vec-style self-supervised context prediction task. The algorithm uses either a gumbel softmax or online k-means clustering to quantize the dense representations... (read more)

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