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.
From ex- periments with a toy example, we conclude that clone-based training can be used to disentangle formants from a signal
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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.