US 2025/0095662 A1 · ROBUST SPREAD-SPECTRUM SPEECH WATERMARKING USING LINEAR PREDICTION AND DEEP SPECTRAL SHAPING

Abstract

Embodiments disclosed herein include software processes executed by a computer for encoding and decoding watermarks for a speech signal in a call signal communicated via telephony channels. An encoder uses Linear Predictive Coding (LPC) to analyzes the call signal's spectral envelope and embeds the watermark into the LPC log-spectrum of the speech signal of the call signal. The encoder may reduce the watermark's strength at a formant peak of the speech signal, balancing the watermark's robustness and detectability. A deep decoder includes a neural network architecture trained on watermarked and watermark-free speech signals having various types of degradation to extract a feature vector of a call signal and compute a watermark detection score for one or more frames or for the call signal. At inference time, the deep decoder detects the watermark when the watermark detection score satisfies a detection threshold.

Claims20

Dependent claims

A computer-implemented method for embedding watermarks in audio signals, comprising:

obtaining, by a computer, a watermarked audio signal comprising a speech signal and a watermark signal embedded at the speech signal;
determining, by the computer, a strength of the watermark signal at a formant peak of the speech signal in the watermarked audio signal;
determining, by the computer, a watermark strength reduction weighting based upon an amount of power of the speech signal at the formant peak;
updating, by the computer, the strength of the watermark signal of the speech signal having the formant peak according to the watermark strength reduction weighting;
and
generating, by the computer, a revised watermarked audio signal comprising the watermark signal having the strength as updated using the watermark strength reduction weighting embedded at the speech signal.

3 more elements

A computer-implemented method for watermark-decoding using machine-learning, comprising:

receiving, by a computer, an inbound call signal for an inbound call that originated via a telephony channel;
generating, by the computer, a transformed representation of the inbound call signal indicating an amount of power at one or more frames in a transform domain at a portion of the inbound call signal;
for each frame, extracting, by the computer, a feature vector of a corresponding frame of the inbound call signal in the transform domain;
generating, by the computer using a neural network architecture of a deep decoder, one or more watermark detection scores for the one or more frames of the inbound call signal using the feature vector of the corresponding frame, wherein the neural network architecture is trained on a plurality of training call signals, including at least one training watermarked call signal and at least one training watermark-free call signal;
identifying, by the computer, a watermark signal being embedded in at least one frame of the inbound call signal in response determining that at least one watermark detection score satisfies a watermark detection threshold;
and
generating, by the computer, a routing instruction indicating a call destination for the inbound call based upon the at least one watermark detection score.

4 more elements

Dependencies are inferred from the claim text.

Robust spread-spectrum speech watermarking using linear prediction and deep spectral shaping

Life of this patent

Robust spread-spectrum speech watermarking using linear prediction and deep spectral shaping

Life of this patent

Abstract

Claims20