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A speech synthesis method, device and electronic equipment

A technology of speech synthesis and subcategories, applied in speech synthesis, speech analysis, instruments, etc., can solve the problems of strong machine sense of sound quality, poor stability outside the set, obvious splicing flaws, etc., and achieve the effect of improving efficiency and effect

Active Publication Date: 2021-08-13
BEIJING SINOVOICE TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The two have their own advantages and disadvantages, and they cannot completely replace each other: voice selection and splicing synthesis have realistic sound quality and real sound length, but the splicing flaws are obvious and the stability outside the set is poor; the statistical parameter synthesis is stable and the synergistic pronunciation is smooth, but the sound quality is strong and machine-like. Length averaging
After all, the reason why parametric synthesis can better balance the fit inside and outside the set and the softness of synergistic pronunciation is at the cost of "melting and flattening" the individuality of the samples in the set, and the details of sound quality and tone will be lost

Method used

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  • A speech synthesis method, device and electronic equipment
  • A speech synthesis method, device and electronic equipment
  • A speech synthesis method, device and electronic equipment

Examples

Experimental program
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Embodiment 1

[0067] figure 1 It is a flowchart of steps of a speech synthesis method provided by an embodiment of the present invention.

[0068] refer to figure 1 As shown, the speech synthesis method provided in this embodiment is applied to electronic devices such as electronic computers or speech synthesis equipment, and specifically includes the following steps:

[0069] S1. Perform text analysis on the input text.

[0070] When the user directly inputs or other electronic equipment inputs the corresponding text, text analysis is performed on the input text, and the target primitive sequence and corresponding context information are obtained therefrom. The target primitive sequence here includes multiple target primitives.

[0071] S2. Using the traditional model decision tree to determine the subcategory number and the corresponding Gaussian distribution model respectively described in the voice selection target model in the context information.

[0072] The voice selection targe...

Embodiment 2

[0150] figure 2 It is a structural block diagram of a speech synthesis device provided by an embodiment of the present invention.

[0151] refer to figure 2 As shown, the speech synthesis device provided by this embodiment is applied to electronic equipment such as electronic computers or speech synthesis equipment, and specifically includes a text analysis module 10, a first calculation module 20, a distance calculation module 30, a grid construction module 40, a second The calculation module 50 , the third calculation module 60 , the fourth calculation module 70 , the path selection module 80 and the splicing output module 90 .

[0152] The text analysis module is used to perform text analysis on the input text.

[0153] When the user directly inputs or other electronic equipment inputs the corresponding text, text analysis is performed on the input text, and the target primitive sequence and corresponding context information are obtained therefrom. The target primitive...

Embodiment 3

[0186] This embodiment provides an electronic device, such as a speech synthesis device, an electronic computer, or a mobile terminal, which is provided with the speech synthesis device provided in the previous embodiment. The device is used to perform text analysis on the input text to obtain the target primitive sequence and the corresponding context information; for the context information, the traditional model decision tree is used to determine the context information in the voice selection target model of the speech library. The subclass number and the corresponding Gaussian distribution model are used to obtain the corresponding pre-selection results; the pre-selection results are used to form a column for each target primitive in turn, and finally the target primitive sequence forms a set of candidate grids; the context information is input into the deep learning model to obtain the acoustic parameter envelope, primitive duration, and boundary frame acoustic parameters ...

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Abstract

Embodiments of the present invention provide a speech synthesis method, device and electronic equipment. This technical solution is to moderately introduce deep learning technology on the sound selection and splicing synthesis route, but does not completely abandon traditional statistical learning technology. The training of the statistical learning model improves the effect of traditional learning from both algorithms and data, thereby improving the effect of speech synthesis.

Description

technical field [0001] The invention relates to the technical field of speech synthesis, in particular to a speech synthesis method, device and electronic equipment. Background technique [0002] In recent years, as the wave of deep learning has swept across the related fields of machine learning, the field of speech synthesis has also been surging. From acoustic parameter modeling, speech enhancement, vocoder, to prosody analysis and other text preprocessing links, they have tried to apply State-of-the-art deep learning techniques, or even attempts to model "end-to-end" directly from text to waveforms, have achieved impressive results. [0003] In the past ten years of development in the field of speech synthesis, the contention between the two routes of statistical parameter synthesis and voice selection splicing synthesis has been maintained. The two have their own strengths and weaknesses, and they cannot completely replace each other: voice selection and splicing synth...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G10L13/02G10L13/08G10L25/30
CPCG10L13/02G10L13/08G10L25/30
Inventor 王愈李健张连毅武卫东
Owner BEIJING SINOVOICE TECH CO LTD
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