公开(公告)号：US20230359818A1

公开(公告)日：2023-11-09

申请号：US18246326

申请日：2020-12-18

Applicant: Google LLC

Inventor： Matthew Sharifi ,  Sebastian Millius ,  Qi Wang ,  Yunpeng Li ,  Shankar Kumar ,  Lukas Zilka ,  Simon Tong ,  Martin Sundermeyer

IPC: G06F40/253

CPC classification number: G06F40/253

Abstract: A computing device may receive inputted text and perform, using one or more neural networks, on-device grammar checking of a sequence of words in the inputted text, including determining, using the one or more neural networks, a grammatically correct version of the sequence of words and determining that the sequence of words does not match the grammatically correct version of the sequence of words. The computing device may, in response to determining that the sequence of words does not match the grammatically correct version of the sequence of words, output, for display at a display device, at least a portion of the grammatically correct version of the sequence of words as a suggested replacement for at least a sequence of the sequence of words in the inputted text.

公开(公告)号：US20230013370A1

公开(公告)日：2023-01-19

申请号：US17856292

申请日：2022-07-01

Applicant: Google LLC

Inventor： Yunpeng Li ,  Marco Tagliasacchi ,  Dominik Roblek ,  Félix de Chaumont Quitry ,  Beat Gfeller ,  Hannah Raphaelle Muckenhirn ,  Victor Ungureanu ,  Oleg Rybakov ,  Karolis Misiunas ,  Zalán Borsos

IPC: G10L19/022 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing an input audio waveform using a generator neural network to generate an output audio waveform. In one aspect, a method comprises: receiving an input audio waveform; processing the input audio waveform using an encoder neural network to generate a set of feature vectors representing the input audio waveform; and processing the set of feature vectors representing the input audio waveform using a decoder neural network to generate an output audio waveform that comprises a respective output audio sample for each of a plurality of output time steps.

公开(公告)号：US20250078848A1

公开(公告)日：2025-03-06

申请号：US18952607

申请日：2024-11-19

Applicant: Google LLC

Inventor： Yunpeng Li ,  Marco Tagliasacchi ,  Dominik Roblek ,  Félix de Chaumont Quitry ,  Beat Gfeller ,  Hannah Raphaelle Muckenhirn ,  Victor Ungureanu ,  Oleg Rybakov ,  Karolis Misiunas ,  Zalán Borsos

IPC: G10L19/022 ,  G06N3/045

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing an input audio waveform using a generator neural network to generate an output audio waveform. In one aspect, a method comprises: receiving an input audio waveform; processing the input audio waveform using an encoder neural network to generate a set of feature vectors representing the input audio waveform; and processing the set of feature vectors representing the input audio waveform using a decoder neural network to generate an output audio waveform that comprises a respective output audio sample for each of a plurality of output time steps.

公开(公告)号：US20240153514A1

公开(公告)日：2024-05-09

申请号：US18548949

申请日：2021-03-05

Applicant: Google LLC

Inventor： Omer Ahmed Siddig Osman ,  Dominik Roblek ,  Yunpeng Li ,  Marco Tagliasacchi ,  Oleg Rybakov ,  Victor Ungureanu ,  Eric Giguere

IPC: G10L19/06 ,  G10L19/16 ,  G10L25/30 ,  G10L25/69

CPC classification number: G10L19/06 ,  G10L19/167 ,  G10L25/30 ,  G10L25/69

Abstract: Apparatus and methods related to enhancement of audio content are provided. An example method includes receiving, by a computing device and via a communications network interface, a compressed audio data frame, wherein the compressed audio data frame is received after transmission over a communications network, The method further includes decompressing the compressed audio data frame to extract an audio waveform. The method also includes predicting, by applying a neural network to the audio waveform, an enhanced version of the audio waveform, wherein the neural network has been trained on (i) a ground truth sample comprising unencoded audio waveforms prior to compression by an audio encoder, and (ii) a training dataset comprising decoded audio waveforms after compression of the unencoded audio waveforms by the audio encoder. The method additionally includes providing, by an audio output component of the computing device, the enhanced version of the audio waveform.

公开(公告)号：US12190896B2

公开(公告)日：2025-01-07

申请号：US17856292

申请日：2022-07-01

Applicant: Google LLC

Inventor： Yunpeng Li ,  Marco Tagliasacchi ,  Dominik Roblek ,  Félix de Chaumont Quitry ,  Beat Gfeller ,  Hannah Raphaelle Muckenhirn ,  Victor Ungureanu ,  Oleg Rybakov ,  Karolis Misiunas ,  Zalán Borsos

IPC: G10L19/022 ,  G06N3/045

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing an input audio waveform using a generator neural network to generate an output audio waveform. In one aspect, a method comprises: receiving an input audio waveform; processing the input audio waveform using an encoder neural network to generate a set of feature vectors representing the input audio waveform; and processing the set of feature vectors representing the input audio waveform using a decoder neural network to generate an output audio waveform that comprises a respective output audio sample for each of a plurality of output time steps.

公开(公告)号：US20230395087A1

公开(公告)日：2023-12-07

申请号：US18249126

申请日：2021-10-15

Applicant: Google LLC

Inventor： Marco Tagliasacchi ,  Beat Gfeller ,  Yunpeng Li ,  Zalán Borsos

IPC: G10L21/007 ,  G10L15/06 ,  G10L15/08 ,  G10L25/18 ,  G10L21/0208 ,  G10L25/21

CPC classification number: G10L21/007 ,  G10L15/063 ,  G10L15/08 ,  G10L25/18 ,  G10L21/0208 ,  G10L25/21 ,  G10L2015/088

Abstract: Example implementations of the present disclosure relate to machine learning for microphone style transfer, for example, to facilitate augmentation of audio data such as speech data to improve robustness of machine learning models trained on the audio data. Systems and methods for microphone style transfer can include one or more machine-learned microphone models trained to obtain and augment signal data to mimic characteristics of signal data obtained from a target microphone. The systems and methods can include a speech enhancement network for enhancing a sample before the style transfer. The augmentation output can then be utilized for a variety of downstream tasks.