Patent · US Active

System and method for discriminative training of regression deep neural networks

US10650806B2 · kind B2 · utility

1Cited by

1References

11Claims

0Family size

Assignee

CERENCE OPERATING COMPANY · US

Inventors

Friedrich Faubel · Ulm, DE
Jonas Sautter · Ulm, DE

Key dates

Filing date	Apr 23, 2018
Grant date	May 12, 2020
Priority date	—
Expiry date	Jun 9, 2038

Classification

Technology area (CPC G)Physics
CPC primaryG10L2025/937
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

A method, computer program product, and computer system for transforming, by a computing device, a speech signal into a speech signal representation. A regression deep neural network may be trained with a cost function to minimize a mean squared error between actual values of the speech signal representation and estimated values of the speech signal representation, wherein the cost function may include one or more discriminative terms. Bandwidth of the speech signal may be extended by extending the speech signal representation of the speech signal using the regression deep neural network trained with the cost function that includes the one or more discriminative terms.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.