公开(公告)号：US11417316B2

公开(公告)日：2022-08-16

申请号：US17115729

申请日：2020-12-08

Applicant: UBTECH ROBOTICS CORP LTD

Inventor： Dongyan Huang ,  Leyuan Sheng ,  Youjun Xiong

IPC: G10L13/08 ,  G10L13/047 ,  G10L25/24

Abstract: The present disclosure provides a speech synthesis method as well as an apparatus and a computer readable storage medium using the same. The method includes: obtaining a to-be-synthesized text, and extracting to-be-processed Mel spectrum features of the to-be-synthesized text through a preset speech feature extraction algorithm; inputting the to-be-processed Mel spectrum features into a preset ResUnet network model to obtain first intermediate features; performing an average pooling and a first down sampling on the to-be-processed Mel spectrum features to obtain second intermediate features; taking the second intermediate features and the first intermediate features output by the ResUnet network model as an input to perform a deconvolution and a first up sampling so as to obtain target Mel spectrum features corresponding to the to-be-processed Mel spectrum features; and converting the target Mel spectrum features into a target speech corresponding to the to-be-synthesized text.

公开(公告)号：US11763796B2

公开(公告)日：2023-09-19

申请号：US17117148

申请日：2020-12-10

Applicant: UBTECH ROBOTICS CORP LTD

Inventor： Dongyan Huang ,  Leyuan Sheng ,  Youjun Xiong

IPC: G10L13/04 ,  G10L13/02 ,  G10L25/30 ,  G10L25/24 ,  G06F17/14 ,  G06N3/08 ,  G06N20/10 ,  G10L21/0324

CPC classification number: G10L13/02 ,  G06F17/14 ,  G06N3/08 ,  G06N20/10 ,  G10L21/0324 ,  G10L25/24 ,  G10L25/30

Abstract: A computer-implemented method for speech synthesis, a computer device, and a non-transitory computer readable storage medium are provided. The method includes: obtaining a speech text to be synthesized; obtaining a Mel spectrum corresponding to the speech text to be synthesized according to the speech text to be synthesized; inputting the Mel spectrum into a complex neural network, and obtaining a complex spectrum corresponding to the speech text to be synthesized, wherein the complex spectrum comprises real component information and imaginary component information; and obtaining a synthetic speech corresponding to the speech text to be synthesized, according to the complex spectrum. The method can efficiently and simply complete speech synthesis.

公开(公告)号：US20220189454A1

公开(公告)日：2022-06-16

申请号：US17117148

申请日：2020-12-10

Applicant: UBTECH ROBOTICS CORP LTD

Inventor： Dongyan Huang ,  Leyuan Sheng ,  Youjun Xiong

IPC: G10L13/02 ,  G10L25/30 ,  G10L25/24 ,  G10L21/0324 ,  G06N3/08 ,  G06N20/10 ,  G06F17/14

Abstract: A computer-implemented method for speech synthesis, a computer device, and a non-transitory computer readable storage medium are provided. The method includes: obtaining a speech text to be synthesized; obtaining a Mel spectrum corresponding to the speech text to be synthesized according to the speech text to be synthesized; inputting the Mel spectrum into a complex neural network, and obtaining a complex spectrum corresponding to the speech text to be synthesized, wherein the complex spectrum comprises real component information and imaginary component information; and obtaining a synthetic speech corresponding to the speech text to be synthesized, according to the complex spectrum. The method can efficiently and simply complete speech synthesis.

公开(公告)号：US20210193113A1

公开(公告)日：2021-06-24

申请号：US17115729

申请日：2020-12-08

Applicant: UBTECH ROBOTICS CORP LTD

Inventor： Dongyan Huang ,  Leyuan Sheng ,  Youjun Xiong

IPC: G10L13/08 ,  G10L25/24 ,  G10L13/047

Abstract: The present disclosure provides a speech synthesis method as well as an apparatus and a computer readable storage medium using the same. The method includes: obtaining a to-be-synthesized text, and extracting to-be-processed Mel spectrum features of the to-be-synthesized text through a preset speech feature extraction algorithm; inputting the to-be-processed Mel spectrum features into a preset ResUnet network model to obtain first intermediate features; performing an average pooling and a first down sampling on the to-be-processed Mel spectrum features to obtain second intermediate features; taking the second intermediate features and the first intermediate features output by the ResUnet network model as an input to perform a deconvolution and a first up sampling so as to obtain target Mel spectrum features corresponding to the to-be-processed Mel spectrum features; and converting the target Mel spectrum features into a target speech corresponding to the to-be-synthesized text.