Deep learning driven multi-channel filtering for speech enhancement
US10546593B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 4, 2017 |
| Grant date | Jan 28, 2020 |
| Priority date | — |
| Expiry date | Apr 16, 2038 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04R3/005
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A number of features are extracted from a current frame of a multi-channel speech pickup and from side information that is a linear echo estimate, a diffuse signal component, or a noise estimate of the multi-channel speech pickup. A DNN-based speech presence probability is produced for the current frame, where the SPP value is produced in response to the extracted features being input to the DNN. The DNN-based SPP value is applied to configure a multi-channel filter whose input is the multi-channel speech pickup and whose output is a single audio signal. In one aspect, the system is designed to run online, at low enough latency for real time applications such voice trigger detection. Other aspects are also described and claimed.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.