Enhancement to Viterbi speech processing algorithm for hybrid speech models that conserves memory
US7805305B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 12, 2006 |
| Grant date | Sep 28, 2010 |
| Priority date | — |
| Expiry date | Jul 29, 2029 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/197
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present invention discloses a method for semantically processing speech for speech recognition purposes. The method can reduce an amount of memory required for a Viterbi search of an N-gram language model having a value of N greater than two and also having at least one embedded grammar that appears in a multiple contexts to a memory size of approximately a bigram model search space with respect to the embedded grammar. The method also reduces needed CPU requirements. Achieved reductions can be accomplished by representing the embedded grammar as a recursive transition network (RTN), where only one instance of the recursive transition network is used for the contexts. Other than the embedded grammars, a Hidden Markov Model (HMM) strategy can be used for the search space.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.