Clone-based training with shared-weight encoders extracts robust 12-dimensional speech features, and these features outperform PCA when used as WaveNet conditioning for coding and enhancement.
Ideally they are distentangled: the system then discovers a ’natural’ set of independent features corre- sponding to ground-truth factors [10]
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Salient Speech Representations Based on Cloned Networks
Clone-based training with shared-weight encoders extracts robust 12-dimensional speech features, and these features outperform PCA when used as WaveNet conditioning for coding and enhancement.