Towards Learning Fine-Grained Disentangled Representations from Speech

August 08, 2018 ยท Declared Dead ยท ๐Ÿ› arXiv.org

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Authors Yuan Gong, Christian Poellabauer arXiv ID 1808.02939 Category cs.SD: Sound Cross-listed cs.CL, cs.LG, eess.AS Citations 6 Venue arXiv.org Last Checked 3 months ago
Abstract
Learning disentangled representations of high-dimensional data is currently an active research area. However, compared to the field of computer vision, less work has been done for speech processing. In this paper, we provide a review of two representative efforts on this topic and propose the novel concept of fine-grained disentangled speech representation learning.
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