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Voice training data iterative updating method based on stage test feedback

A technology of iterative update and speech training, applied in speech analysis, speech recognition, instruments, etc., can solve problems such as performance degradation

Active Publication Date: 2021-08-06
ZHEJIANG UNIV
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  • Claims
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AI Technical Summary

Problems solved by technology

The existing experimental research on synthetic speech detection is trained according to the training set set by the competition, usually using a large amount of training data; however, in actual situations, when more training data is used, the performance is improved. Decline, because there is redundancy in the training data, it is necessary to perform data selection

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  • Voice training data iterative updating method based on stage test feedback

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Embodiment Construction

[0023] The present invention is applicable to speech classification scenarios such as speech recognition, speaker recognition, forged speech recognition and the like. In order to further understand the present invention, the technical solution of the present invention will be described in detail below only with regard to the application specific embodiment of selecting the core training speech in synthetic speech detection, but it should be understood that these descriptions are only for further illustrating the features and advantages of the present invention, and It is not a limitation of the claims of the invention.

[0024] The experimental data used in this embodiment is the logical access database of the 2019 Automatic Speaker Recognition Deception Attack and Defense Countermeasure Challenge (ASVspoof 2019-LA), and the 2015 Automatic Speaker Recognition Deception Attack and Defense Countermeasure Challenge (ASVspoof 2015) and Real Scene Synthetic Speech Detection Dataset...

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Abstract

The invention discloses a voice training data iterative updating method based on stage test feedback, which comprises the steps of training by continuously adding misrecognition voice in stage test voice to establish a reference model, then calculating the likelihood score of the original training voice on the reference model, then sorting various voices according to the likelihood score, and selecting the sorted voices according to a certain proportion to obtain stage core training voices. Through the voice training data iterative updating method provided by the invention, high-quality training voices can be continuously screened according to the feedback of test data, and the obtained stage core training voices utilize stage application feedback in time, so that the future recognition performance of the stage core training voices is better and better; and the method is suitable for voice classification scenes such as voice recognition, speaker recognition and forged voice recognition.

Description

technical field [0001] The invention belongs to the technical field of speech recognition, in particular to a method for iteratively updating speech training data based on stage test feedback. Background technique [0002] As a biometric authentication method, the voiceprint authentication system has the advantages of low acquisition cost, easy access, and convenient remote authentication. It has been widely used in access control systems, financial transactions, judicial identification, and other fields. With the rapid development of speech synthesis technology, on the one hand, it has brought more convenient services and better user experience to people, such as Zhensheng intelligent customer service, Zhensheng intelligent navigation, audio books, intelligent voice calls, etc.; It brings great challenges to the security of the voiceprint authentication system, such as using synthetic voice to attack the voiceprint authentication system to make its performance significantly...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G10L17/04G10L15/06
CPCG10L17/04G10L15/063
Inventor 杨莹春魏含玉吴朝晖
Owner ZHEJIANG UNIV
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