US 12,087,319 B1
Joint estimation of acoustic parameters from single-microphone speech
David Looney, Atlanta, GA (US); and Nikolay Gaubitch, Atlanta, GA (US)
Assigned to Pindrop Security, Inc., Atlanta, GA (US)
Filed by PINDROP SECURITY, INC., Atlanta, GA (US)
Filed on Oct. 23, 2020, as Appl. No. 17/079,082.
Claims priority of provisional application 62/925,349, filed on Oct. 24, 2019.
Int. Cl. G10L 25/30 (2013.01); G06N 3/048 (2023.01); G06N 3/08 (2023.01)
CPC G10L 25/30 (2013.01) [G06N 3/048 (2023.01); G06N 3/08 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for end-to-end acoustic degradation estimation from an audio signal comprising:
training, by a computer, a neural network architecture by applying the neural network architecture on a plurality of simulated audio signals having one or more types of degradation, the neural network architecture comprising a plurality of sets of one or more layers to generate a corresponding degradation parameter score;
receiving, by the computer, an input audio signal originating from a speaker; and
generating, by the computer, a plurality of degradation parameter scores for the input audio signal based upon a plurality of degradation parameters corresponding to a type of degradation by applying the neural network architecture to the input audio signal,
wherein a first degradation parameter score of the plurality of degradation parameter scores is output by a first set of one or more layers of the neural network architecture and fed to a second set of one or more layers of the neural network architecture to generate a second degradation parameter score of the plurality of degradation parameter scores.