公开(公告)号：US20250054500A1

公开(公告)日：2025-02-13

申请号：US18233323

申请日：2023-08-13

Applicant: Google LLC

Inventor： Hakan Erdogan ,  Scott Thomas Wisdom ,  John Hershey ,  Zalán Borsos ,  Marco Tagliasacchi ,  Neil Zeghidour ,  Xuankai Chang

IPC: G10L17/20 ,  G10L17/02 ,  G10L17/04 ,  G10L17/06 ,  G10L17/18

Abstract: A system and method are disclosed. Audio input comprising the mixed audio signals is received by one or more client devices. The audio input is converted into a plurality of discrete tokens. A plurality of sound sources, each corresponding to a subset of discrete tokens of a plurality of subsets of discrete tokens, is determined using a trained machine learning model.

公开(公告)号：US11238847B2

公开(公告)日：2022-02-01

申请号：US17251163

申请日：2019-12-04

Applicant: GOOGLE LLC

Inventor： Ignacio Lopez Moreno ,  Quan Wang ,  Jason Pelecanos ,  Li Wan ,  Alexander Gruenstein ,  Hakan Erdogan

IPC: G10L17/00 ,  G10L15/06 ,  G10L15/07 ,  G10L15/20 ,  G10L17/04 ,  G10L17/20 ,  G10L21/0208 ,  G10L15/08

Abstract: Techniques disclosed herein enable training and/or utilizing speaker dependent (SD) speech models which are personalizable to any user of a client device. Various implementations include personalizing a SD speech model for a target user by processing, using the SD speech model, a speaker embedding corresponding to the target user along with an instance of audio data. The SD speech model can be personalized for an additional target user by processing, using the SD speech model, an additional speaker embedding, corresponding to the additional target user, along with another instance of audio data. Additional or alternative implementations include training the SD speech model based on a speaker independent speech model using teacher student learning.

公开(公告)号：US20240249741A1

公开(公告)日：2024-07-25

申请号：US18159679

申请日：2023-01-25

Applicant: Google LLC

Inventor： George Chiachi Sung ,  Yang Yang ,  Shao-Fu Shih ,  Hakan Erdogan ,  Jamie Menjay Lin

IPC: G10L21/0232 ,  G10L15/06 ,  G10L15/16 ,  G10L15/22 ,  G10L21/0308 ,  G10L25/18

CPC classification number: G10L21/0232 ,  G10L15/063 ,  G10L15/16 ,  G10L15/22 ,  G10L21/0308 ,  G10L25/18 ,  G10L2021/02082

Abstract: A method includes receiving, as input, reference audio data representing a reference audio signal captured by an audio input device. The method also includes receiving, as input, from a beamformer, spatially-filtered audio data representing an output of the beamformer, the beamformer configured to spatially filter, based on additional audio data captured by one or more additional audio input devices, the reference audio data to attenuate one or more interfering signals in the spatially-filtered audio data. The method processes, using a trained guided speech-enhancement network, the reference audio data and the spatially-filtered audio data to generate, as output, enhanced audio data, the guided speech-enhancement network processing the reference audio data and the spatially-filtered audio data to further attenuate, in the enhanced audio data, the one or more interfering signals attenuated by the beamformer.

公开(公告)号：US20240203400A1

公开(公告)日：2024-06-20

申请号：US18394632

申请日：2023-12-22

Applicant: GOOGLE LLC

Inventor： Ignacio Lopez Moreno ,  Quan Wang ,  Jason Pelecanos ,  Li Wan ,  Alexander Gruenstein ,  Hakan Erdogan

IPC: G10L15/06 ,  G10L15/07 ,  G10L15/08 ,  G10L15/20 ,  G10L17/04 ,  G10L17/20 ,  G10L21/0208

CPC classification number: G10L15/063 ,  G10L15/07 ,  G10L15/20 ,  G10L17/04 ,  G10L17/20 ,  G10L21/0208 ,  G10L2015/088

Abstract: Implementations relate to an automated assistant that can bypass invocation phrase detection when an estimation of device-to-device distance satisfies a distance threshold. The estimation of distance can be performed for a set of devices, such as a computerized watch and a cellular phone, and/or any other combination of devices. The devices can communicate ultrasonic signals between each other, and the estimated distance can be determined based on when the ultrasonic signals are sent and/or received by each respective device. When an estimated distance satisfies the distance threshold, the automated assistant can operate as if the user is holding onto their cellular phone while wearing their computerized watch. This scenario can indicate that the user may be intending to hold their device to interact with the automated assistant and, based on this indication, the automated assistant can temporarily bypass invocation phrase detection (e.g., invoke the automated assistant).

公开(公告)号：US11854533B2

公开(公告)日：2023-12-26

申请号：US17587424

申请日：2022-01-28

Applicant: GOOGLE LLC

Inventor： Ignacio Lopez Moreno ,  Quan Wang ,  Jason Pelecanos ,  Li Wan ,  Alexander Gruenstein ,  Hakan Erdogan

IPC: G10L15/16 ,  G10L15/06 ,  G10L15/07 ,  G10L15/20 ,  G10L17/04 ,  G10L17/20 ,  G10L21/0208 ,  G10L15/08

CPC classification number: G10L15/063 ,  G10L15/07 ,  G10L15/20 ,  G10L17/04 ,  G10L17/20 ,  G10L21/0208 ,  G10L2015/088

Abstract: Techniques disclosed herein enable training and/or utilizing speaker dependent (SD) speech models which are personalizable to any user of a client device. Various implementations include personalizing a SD speech model for a target user by processing, using the SD speech model, a speaker embedding corresponding to the target user along with an instance of audio data. The SD speech model can be personalized for an additional target user by processing, using the SD speech model, an additional speaker embedding, corresponding to the additional target user, along with another instance of audio data. Additional or alternative implementations include training the SD speech model based on a speaker independent speech model using teacher student learning.

公开(公告)号：US20220157298A1

公开(公告)日：2022-05-19

申请号：US17587424

申请日：2022-01-28

Applicant: GOOGLE LLC

Inventor： Ignacio Lopez Moreno ,  Quan Wang ,  Jason Pelecanos ,  Li Wan ,  Alexander Gruenstein ,  Hakan Erdogan

IPC: G10L15/06 ,  G10L15/07 ,  G10L15/20 ,  G10L17/04 ,  G10L17/20 ,  G10L21/0208

Abstract: Techniques disclosed herein enable training and/or utilizing speaker dependent (SD) speech models which are personalizable to any user of a client device. Various implementations include personalizing a SD speech model for a target user by processing, using the SD speech model, a speaker embedding corresponding to the target user along with an instance of audio data. The SD speech model can be personalized for an additional target user by processing, using the SD speech model, an additional speaker embedding, corresponding to the additional target user, along with another instance of audio data. Additional or alternative implementations include training the SD speech model based on a speaker independent speech model using teacher student learning.

公开(公告)号：US20210312907A1

公开(公告)日：2021-10-07

申请号：US17251163

申请日：2019-12-04

Applicant: GOOGLE LLC

Inventor： Ignacio Lopez Moreno ,  Quan Wang ,  Jason Pelecanos ,  Li Wan ,  Alexander Gruenstein ,  Hakan Erdogan

IPC: G10L15/06 ,  G10L15/07 ,  G10L21/0208 ,  G10L15/20 ,  G10L17/04 ,  G10L17/20

Abstract: Techniques disclosed herein enable training and/or utilizing speaker dependent (SD) speech models which are personalizable to any user of a client device. Various implementations include personalizing a SD speech model for a target user by processing, using the SD speech model, a speaker embedding corresponding to the target user along with an instance of audio data. The SD speech model can be personalized for an additional target user by processing, using the SD speech model, an additional speaker embedding, corresponding to the additional target user, along with another instance of audio data. Additional or alternative implementations include training the SD speech model based on a speaker independent speech model using teacher student learning.