METHOD AND SYSTEM FOR GENERATING ADVANCED FEATURE DISCRIMINATION VECTORS FOR USE IN SPEECH RECOGNITION
Patent №
US 9,728,182
Granted
2017-08-08
Filed 2014
Owner
SETEM TECHNOLOGIES, INC.
Lab
—
AI components
3
ml · nlp · speech
Assignment
Recorded
Dataset
AIPD
2023_r1 edition
Application
14217198
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.
AI classification
Ownership
SETEM TECHNOLOGIES, INC.
assignment · 400690954
Assignors
SHORT, KEVIN M., HONE, BRIAN T.
On an employer assignment, the assignors are typically the inventors.