- Patent Title: Deep learning driven multi-channel filtering for speech enhancement
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Application No.: US15830955Application Date: 2017-12-04
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Publication No.: US10546593B2Publication Date: 2020-01-28
- Inventor: Jason Wung , Mehrez Souden , Ramin Pishehvar , Joshua D. Atkins
- Applicant: Apple Inc.
- Applicant Address: US CA Cupertino
- Assignee: APPLE INC.
- Current Assignee: APPLE INC.
- Current Assignee Address: US CA Cupertino
- Agency: Womble Bond Dickinson (US) LLP
- Main IPC: G10L21/00
- IPC: G10L21/00 ; G10L19/00 ; G10L21/02 ; G10L15/02 ; G10L21/0232 ; G10L25/30 ; H04R1/40 ; G10L25/03 ; G10L21/0208

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.
Public/Granted literature
- US20190172476A1 DEEP LEARNING DRIVEN MULTI-CHANNEL FILTERING FOR SPEECH ENHANCEMENT Public/Granted day:2019-06-06
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