Method and system for generating advanced feature discrimination vectors for use in speech recognition
US10410623B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 30, 2017 |
| Grant date | Sep 10, 2019 |
| Priority date | — |
| Expiry date | Jun 30, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L2015/025
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method of renormalizing high-resolution oscillator peaks, extracted from windowed samples of an audio signal, is disclosed. Feature vectors are generated for which variations in both fundamental frequency and time duration of speech are substantially mitigated. The feature vectors may be aligned within a common coordinate space, free of those variations in frequency and time duration that occurs between speakers, and even over speech by a single speaker, to facilitate a simple and accurate determination of matches between those AFDVs generated from a sample of the audio signal and corpus AFDVs generated for known speech at the phoneme and sub-phoneme level. The renormalized feature vectors can be combined with traditional feature vectors such as MFCCs, or they can be used exclusively to identify voiced, semi-voiced and unvoiced sounds.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.