Unsupervised Learning of Disentangled Speech Content and Style Representation

Andros Tjandra
Andros Tjandra
Shigeki Karita
Shigeki Karita
Cited by: 0|Bibtex|Views10
Other Links: arxiv.org

Abstract:

We present an approach for unsupervised learning of speech representation disentangling contents and styles. Our model consists of: (1) a local encoder that captures per-frame information; (2) a global encoder that captures per-utterance information; and (3) a conditional decoder that reconstructs speech given local and global latent va...More

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