Adaptive speech recognition with selective input data to a speech classifier
US6044343A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | Jun 27, 1997 |
| Grant date | Mar 28, 2000 |
| Priority date | — |
| Expiry date | Jun 27, 2017 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
One embodiment of a speech recognition system is organized with speech input signal preprocessing and feature extraction followed by a fuzzy matrix quantizer (FMQ) designed with respective codebook sets at multiple signal to noise ratios. The FMQ quantizes various training words from a set of vocabulary words and produces observation sequences O output data to train a hidden Markov model (HMM) processes .lambda.j and produces fuzzy distance measure output data for each vocabulary word codebook. A fuzzy Viterbi algorithm is used by a processor to compute maximum likelihood probabilities PR(O.vertline..lambda.j) for each vocabulary word. The fuzzy distance measures and maximum likelihood probabilities are mixed in a variety of ways to preferably optimize speech recognition accuracy and speech recognition speed performance.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.