Presentation | 2014-07-25 Voice conversion based on sparse representation and its application to articulation disorders Tetsuya TAKIGUCHI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In recent years, approaches based on sparse representations have gained interest in a broad range of signal processing. For example, Non-negative Matrix Factorization (NMF) is a well-known sparse-based approach for source separation and speech enhancement. In this paper, a voice conversion technique based on a sparse representation of speech using NMF is introduced, and it is applied to a person with an articulation disorder resulting from athetoid cerebral palsy. Also, in this paper, a voice conversion method using restricted Boltzmann machine, which is an important technique for deep learning, is introduced. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | voice conversion / sparse representation / articulation disorder / restricted Boltzmann machine |
Paper # | SP2014-66 |
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Committee | SP |
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Conference Date | 2014/7/17(1days) |
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Registration To | Speech (SP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Voice conversion based on sparse representation and its application to articulation disorders |
Sub Title (in English) | |
Keyword(1) | voice conversion |
Keyword(2) | sparse representation |
Keyword(3) | articulation disorder |
Keyword(4) | restricted Boltzmann machine |
1st Author's Name | Tetsuya TAKIGUCHI |
1st Author's Affiliation | Organization of Advanced Science and Technology, Kobe University() |
Date | 2014-07-25 |
Paper # | SP2014-66 |
Volume (vol) | vol.114 |
Number (no) | 151 |
Page | pp.pp.- |
#Pages | 6 |
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