Statistical post-filtering for hidden Markov modeling (HMM)-based speech synthesis
US9159329B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 5, 2012 |
| Grant date | Oct 13, 2015 |
| Priority date | — |
| Expiry date | Dec 31, 2033 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L13/04
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method and system for improving the quality of speech generated from Hidden Markov Model (HMM)-based Text-To-Speech Synthesizers using statistical post-filtering techniques. An example method involves: (a) determining a scale factor that, when applied to a synthesized reference spectral envelope, minimizes a statistical divergence between a natural reference spectral envelope and the synthesized reference spectral envelope, where the synthesized reference spectral envelope is generated by a state of an HMM; (b) for a given synthesized subject spectral envelope generated by the state of the HMM, determining an enhanced synthesized subject spectral envelope based on the determined scale factor; and (c) generating, by a computing device, a synthetic speech signal including the enhanced synthesized subject spectral envelope.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.