Senone tree representation and evaluation
US5794197A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | May 2, 1997 |
| Grant date | Aug 11, 1998 |
| Priority date | — |
| Expiry date | May 2, 2017 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L2015/0631
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A speech recognition method provides improved modeling in recognition accuracy using hidden Markov models. During training, the method creates a senone tree for each state of each phoneme encountered in a data set of training words. All output distributions received for a selected state of a selected phoneme in the set of training words are clustered together in a root node of a senone tree. Each node of the tree beginning with the root node is divided into two nodes by asking linguistic questions regarding the phonemes immediately to the left and right of a central phoneme of a triphone. At a predetermined point, the tree creation stops, resulting in leaves representing clustered output distributions known as senones. The senone trees allow all possible triphones to be mapped into a sequence of senones simply by traversing the senone trees associated with the central phoneme of the triphone. As a result, unseen triphones not encountered in the training data can be modeled with senones created using the triphones actually found in the training data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.