Hidden markov model for speech processing with training method
US9020816B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Aug 13, 2009 |
| Grant date | Apr 28, 2015 |
| Priority date | — |
| Expiry date | Jul 26, 2032 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L25/24
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method, system and apparatus are shown for identifying non-language speech sounds in a speech or audio signal. An audio signal is segmented and feature vectors are extracted from the segments of the audio signal. The segment is classified using a hidden Markov model (HMM) that has been trained on sequences of these feature vectors. Post-processing components can be utilized to enhance classification. An embodiment is described in which the hidden Markov model is used to classify a segment as a language speech sound or one of a variety of non-language speech sounds. Another embodiment is described in which the hidden Markov model is trained using discriminative learning.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.