Name
Abstract | ||
|---|---|---|
Current model-based speech analysis tends to be incomplete - only a part of parameters of interest (e.g. only the pitch or vocal tract) are modeled, while the rest that might as well be important are disregarded. The drawback is that without joint modeling of parameters that are correlated, the analysis on speech parameters may be inaccurate or even incorrect. Under this motivation, we have proposed such a model called PAT (Probabilistic Acoustic Tube), where pitch, vocal tract and energy are jointly modeled. This paper proposes an improved version of PAT model, named PAT2, where both signal and probabilistic modeling are tremendously renovated. Compared to related works, PAT2 is much more comprehensive, which incorporates mixed excitation, glottal wave and phase modeling. Experimental results show its ability in decomposing speech into desirable parameters and its potential for speech synthesis. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICASSP.2014.6855144 | ICASSP |
Keywords | Field | DocType |
signal modeling,speech processing,probabilistic generative model,probabilistic acoustic tube model,speech analysis,speech parameters,pat2,probabilistic modeling,pat model,speech decomposition,model-based speech processing,vocal tract,speech modeling,probability,mel frequency cepstral coefficient,image reconstruction,speech,probabilistic logic | Speech synthesis,Speech coding,Computer science,Speech modeling,Speech recognition,Probabilistic generative model,Probabilistic logic,Vocal tract,Linear predictive coding,Acoustic model | Conference |
ISSN | Citations | PageRank |
1520-6149 | 1 | 0.41 |
References | Authors | |
8 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yang Zhang | 1 | 39 | 5.01 |
| Zhijian Ou | 2 | 57 | 19.29 |
| Mark Hasegawa-Johnson | 3 | 1189 | 112.85 |