公开(公告)号：US11769480B2

公开(公告)日：2023-09-26

申请号：US17111238

申请日：2020-12-03

Applicant: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.

Inventor： Zhengkun Gao ,  Junteng Zhang ,  Wenfu Wang ,  Tao Sun

IPC: G10L13/00 ,  G10L13/047 ,  G10L13/06 ,  G10L13/10

CPC classification number: G10L13/047 ,  G10L13/06 ,  G10L13/10

Abstract: The present disclosure discloses a method and apparatus for training a model, a method and apparatus for synthesizing a speech, a device and a storage medium, and relates to the field of natural language processing and deep learning technology. The method for training a model may include: determining a phoneme feature and a prosodic word boundary feature of sample text data; inserting a pause character into the phoneme feature according to the prosodic word boundary feature to obtain a combined feature of the sample text data; and training an initial speech synthesis model according to the combined feature of the sample text data, to obtain a target speech synthesis model.

公开(公告)号：US11488578B2

公开(公告)日：2022-11-01

申请号：US17205121

申请日：2021-03-18

Applicant: Beijing Baidu Netcom Science and Technology Co., Ltd.

Inventor： Zhijie Chen ,  Tao Sun ,  Lei Jia

IPC: G10L13/00 ,  G10L13/047 ,  G10L13/10 ,  G10L25/18 ,  G10L25/30

Abstract: The present application discloses a method and an apparatus for training a speech spectrum generation model, as well as an electronic device, and relates to the technical field of speech synthesis and deep learning. A specific implementation is as follows: inputting a first text sequence into the speech spectrum generation model to generate an analog spectrum sequence corresponding to the first text sequence, and obtain a first loss value of the analog spectrum sequence according to a preset loss function; inputting the analog spectrum sequence corresponding to the first text sequence into an adversarial loss function model, which is a generative adversarial network model, to obtain a second loss value of the analog spectrum sequence; and training the speech spectrum generation model based on the first loss value and the second loss value.