Text-independent speaker verification method and device

Abstract

The invention discloses a text-independent speaker verification method and a text-independent speaker verification device. The method comprises the steps of extracting the amplitude features of to-be-verified voice and phase features corresponding to the amplitude features; processing the amplitude characteristics and the phase characteristics to obtain phase perception characteristics; speaker classification is carried out on the phase perception features to obtain speaker embedding; and performing probability linear judgment analysis on the speaker embedding to obtain a speaker verificationresult of the to-be-verified voice. According to the scheme provided by the invention, the amplitude features and the phase features are combined in deep speaker embedding learning, so that the noiserobustness of the speaker verification system can be improved. Furthermore, the scheme of the invention not only provides a new scheme for a speaker verification system with robust noise, but also shows various possibilities of improving performance by using phase characteristics.

Description

technical field

[0001] The invention belongs to the technical field of speaker verification, in particular to a text-independent speaker verification method and device. Background technique

[0002] In related technologies, the existing speaker verification systems are roughly divided into two schools: 1) based on the traditional i-vector model; 2) based on the deep learning framework. However, the existing speaker verification systems on the market usually require the same environment for training and testing. If the testing environment is noisy, its performance will be greatly reduced. Currently, most of the noise-robust speaker verification systems on the market are trained by constructing noisy datasets. Existing speaker verification systems that combine phase information are also based on traditional speaker verification system frameworks (Gaussian mixture models, etc.).

[0003] The traditional i-vector system models the speaker through GMM (gaussian mixture model, G...

Examples

Embodiment Construction

[0022] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0023] Please refer to figure 1 , which shows the flowchart of an embodiment of the text-independent speaker verification method of the present application, the text-independent speaker verification method of this embodiment can be applied to terminals with language models, such as smart voice TVs, smart speakers, smart dialogue Toys and other ex...

technical field

[0001] The invention belongs to the technical field of speaker verification, in particular to a text-independent speaker verification method and device. Background technique

[0002] In related technologies, the existing speaker verification systems are roughly divided into two schools: 1) based on the traditional i-vector model; 2) based on the deep learning framework. However, the existing speaker verification systems on the market usually require the same environment for training and testing. If the testing environment is noisy, its performance will be greatly reduced. Currently, most of the noise-robust speaker verification systems on the market are trained by constructing noisy datasets. Existing speaker verification systems that combine phase information are also based on traditional speaker verification system frameworks (Gaussian mixture models, etc.).

[0003] The traditional i-vector system models the speaker through GMM (gaussian mixture model, G...

Examples

Embodiment Construction

[0022] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0023] Please refer to figure 1 , which shows the flowchart of an embodiment of the text-independent speaker verification method of the present application, the text-independent speaker verification method of this embodiment can be applied to terminals with language models, such as smart voice TVs, smart speakers, smart dialogue Toys and other ex...

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