Name
Abstract | ||
|---|---|---|
Articulatory speech synthesis has the potential to offer more natural sounding synthetic speech than established concatenative or parametric synthesis methods. Time-domain acoustic models are particularly suited to the dynamic nature of the speech signal, and recent work has demonstrated the potential of dynamic vocal tract models that accurately reproduce the vocal tract geometry. This paper pres... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TASLP.2017.2774921 | IEEE/ACM Transactions on Audio, Speech, and Language Processing |
Keywords | Field | DocType |
Speech,Computational modeling,Junctions,Hidden Markov models,Time-domain analysis,Acoustics | Speech synthesis,Pattern recognition,Computer science,Waveguide,Speech recognition,Parametric statistics,Artificial intelligence,Diphthong,Formant,Hidden Markov model,Vocal tract,Dynamic simulation | Journal |
Volume | Issue | ISSN |
26 | 2 | 2329-9290 |
Citations | PageRank | References |
0 | 0.34 | 15 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amelia J. Gully | 1 | 0 | 0.68 |
| Helena Daffern | 2 | 0 | 1.35 |
| Damian T. Murphy | 3 | 26 | 6.28 |