Neural-echo: an unified deep neural network model for acoustic echo cancellation and residual echo suppression
US12293769B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 21, 2023 |
| Grant date | May 6, 2025 |
| Priority date | — |
| Expiry date | Aug 21, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L2021/02163
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method, computer program, and computer system is provided for an all-deep-learning based AEC system by recurrent neural networks. The model consists of two stages, echo estimation stage and echo suppression stage, respectively. Two different schemes for echo estimation are presented herein: linear echo estimation by multi-tap filtering on far-end reference signal and non-linear echo estimation by single-tap masking on microphone signal. A microphone signal waveform and a far-end reference signal waveform are received. An echo signal waveform is estimated based on the microphone signal waveform and a far-end reference signal waveform. A near-end speech signal waveform is output based on subtracting the estimated echo signal waveform from the microphone signal waveform, and echoes are suppressed within the near-end speech signal waveform.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.