公开(公告)号：US11996114B2

公开(公告)日：2024-05-28

申请号：US17321411

申请日：2021-05-15

Applicant: Apple Inc.

Inventor： Ramin Pishehvar ,  Ante Jukic ,  Mehrez Souden ,  Jason Wung ,  Feipeng Li ,  Joshua D. Atkins

IPC: G10L15/16 ,  G06N20/00 ,  G10L21/0216

CPC classification number: G10L21/0216 ,  G06N20/00 ,  G10L15/16 ,  G10L2021/02166

Abstract: Disclosed is a multi-task machine learning model such as a time-domain deep neural network (DNN) that jointly generate an enhanced target speech signal and target audio parameters from a mixed signal of target speech and interference signal. The DNN may encode the mixed signal, determine masks used to jointly estimate the target signal and the target audio parameters based on the encoded mixed signal, apply the mask to separate the target speech from the interference signal to jointly estimate the target signal and the target audio parameters, and decode the masked features to enhance the target speech signal and to estimate the target audio parameters. The target audio parameters may include a voice activity detection (VAD) flag of the target speech. The DNN may leverage multi-channel audio signal and multi-modal signals such as video signals of the target speaker to improve the robustness of the enhanced target speech signal.

公开(公告)号：US11532306B2

公开(公告)日：2022-12-20

申请号：US17111132

申请日：2020-12-03

Applicant: Apple Inc.

Inventor： Yoon Kim ,  John Bridle ,  Joshua D. Atkins ,  Feipeng Li ,  Mehrez Souden

IPC: G10L15/22 ,  H04R1/40 ,  G10L15/08 ,  G10L15/04 ,  H04R3/00 ,  G10L15/30 ,  G10L15/18 ,  G10L15/28 ,  G10L21/0216 ,  G10L25/51 ,  H04R27/00

Abstract: Systems and processes for operating an intelligent automated assistant are provided. In accordance with one example, a method includes, at an electronic device with one or more processors, memory, and a plurality of microphones, sampling, at each of the plurality of microphones of the electronic device, an audio signal to obtain a plurality of audio signals; processing the plurality of audio signals to obtain a plurality of audio streams; and determining, based on the plurality of audio streams, whether any of the plurality of audio signals corresponds to a spoken trigger. The method further includes, in accordance with a determination that the plurality of audio signals corresponds to the spoken trigger, initiating a session of the digital assistant; and in accordance with a determination that the plurality of audio signals does not correspond to the spoken trigger, foregoing initiating a session of the digital assistant.

公开(公告)号：US20220366927A1

公开(公告)日：2022-11-17

申请号：US17321411

申请日：2021-05-15

Applicant: Apple Inc.

Inventor： Ramin Pishehvar ,  Ante Jukic ,  Mehrez Souden ,  Jason Wung ,  Feipeng Li ,  Joshua D. Atkins

IPC: G10L21/0216 ,  G10L15/16 ,  G06N20/00

Abstract: Disclosed is a multi-task machine learning model such as a time-domain deep neural network (DNN) that jointly generate an enhanced target speech signal and target audio parameters from a mixed signal of target speech and interference signal. The DNN may encode the mixed signal, determine masks used to jointly estimate the target signal and the target audio parameters based on the encoded mixed signal, apply the mask to separate the target speech from the interference signal to jointly estimate the target signal and the target audio parameters, and decode the masked features to enhance the target speech signal and to estimate the target audio parameters. The target audio parameters may include a voice activity detection (VAD) flag of the target speech. The DNN may leverage multi-channel audio signal and multi-modal signals such as video signals of the target speaker to improve the robustness of the enhanced target speech signal.

公开(公告)号：US20200312315A1

公开(公告)日：2020-10-01

申请号：US16368403

申请日：2019-03-28

Applicant: Apple Inc.

Inventor： Feipeng Li ,  Mehrez Souden ,  Joshua D. Atkins ,  John Bridle ,  Charles P. Clark ,  Stephen H. Shum ,  Sachin S. Kajarekar ,  Haiying Xia ,  Erik Marchi

IPC: G10L15/20

Abstract: An acoustic environment aware method for selecting a high quality audio stream during multi-stream speech recognition. A number of input audio streams are processed to determine if a voice trigger is detected, and if so a voice trigger score is calculated for each stream. An acoustic environment measurement is also calculated for each audio stream. The trigger score and acoustic environment measurement are combined for each audio stream, to select as a preferred audio stream the audio stream with the highest combined score. The preferred audio stream is output to an automatic speech recognizer. Other aspects are also described and claimed.