Robust spoofing detection system using deep residual neural networks
US12417772B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 22, 2023 |
| Grant date | Sep 16, 2025 |
| Priority date | — |
| Expiry date | Dec 22, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L17/22
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments described herein provide for systems and methods for implementing a neural network architecture for spoof detection in audio signals. The neural network architecture contains a layers defining embedding extractors that extract embeddings from input audio signals. Spoofprint embeddings are generated for particular system enrollees to detect attempts to spoof the enrollee's voice. Optionally, voiceprint embeddings are generated for the system enrollees to recognize the enrollee's voice. The voiceprints are extracted using features related to the enrollee's voice. The spoofprints are extracted using features related to features of how the enrollee speaks and other artifacts. The spoofprints facilitate detection of efforts to fool voice biometrics using synthesized speech (e.g., deepfakes) that spoof and emulate the enrollee's voice.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.