Name
Title | ||
|---|---|---|
Individuality-preserving voice conversion for articulation disorders based on non-negative matrix factorization |
Abstract | ||
|---|---|---|
We present in this paper a voice conversion (VC) method for a person with an articulation disorder resulting from athetoid cerebral palsy. The movement of such speakers is limited by their athetoid symptoms, and their consonants are often unstable or unclear, which makes it difficult for them to communicate. In this paper, exemplar-based spectral conversion using Non-negative Matrix Factorization (NMF) is applied to a voice with an articulation disorder. To preserve the speaker's individuality, we used a combined dictionary that is constructed from the source speaker's vowels and target speaker's consonants. Experimental results indicate that the performance of NMF-based VC is considerably better than conventional GMM-based VC. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICASSP.2013.6639230 | Acoustics, Speech and Signal Processing |
Keywords | Field | DocType |
matrix decomposition,speech enhancement,NMF-based VC,articulation disorders,athetoid cerebral palsy,athetoid symptoms,combined dictionary,exemplar-based spectral conversion,individuality-preserving voice conversion,nonnegative matrix factorization,Articulation Disorders,Assistive Technologies,NMF,Voice Conversion,Voice Reconstruction | Athetoid cerebral palsy,Speech enhancement,Pattern recognition,Computer science,Articulation Disorders,Matrix decomposition,Speech recognition,Non-negative matrix factorization,Artificial intelligence | Conference |
ISSN | Citations | PageRank |
1520-6149 | 9 | 0.52 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aihara, R. | 1 | 16 | 0.98 |
| Ryoichi Takashima | 2 | 95 | 12.16 |
| Tetsuya Takiguchi | 3 | 85 | 8.77 |
| Yasuo Ariki | 4 | 519 | 88.94 |