Probability linear speaker-distinguishing identifying method based on priori knowledge structured covariance

A technology for speaker identification and linear identification, which is applied in the field of speaker identification based on probabilistic linear identification analysis based on prior knowledge normalization and covariance, which can solve problems such as erasure and achieve the effect of improving the effect.

Active Publication Date: 2015-12-09
SYSU CMU SHUNDE INT JOINT RES INST +1
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Problems solved by technology

[0007] However, the limitation of the above algorithm framework is that the frame length and signal-to-noise ratio of each speech are different, and the probabilistic linear discriminant analysis model trained by using the global cov...

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  • Probability linear speaker-distinguishing identifying method based on priori knowledge structured covariance
  • Probability linear speaker-distinguishing identifying method based on priori knowledge structured covariance
  • Probability linear speaker-distinguishing identifying method based on priori knowledge structured covariance

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[0031] The drawings are for illustrative purposes only, and should not be construed as limitations on this patent; in order to better illustrate this embodiment, some parts in the drawings will be omitted, enlarged or reduced, and do not represent the size of the actual product;

[0032] For those skilled in the art, it is understandable that some well-known structures and descriptions thereof may be omitted in the drawings. The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0033] figure 1 In the present invention, the inherent physical information of the training speech, such as duration, signal-to-noise ratio, and scoring information obtained from other models, is used as a regularization process for the prior knowledge of this model training. In this embodiment, the duration of the training speech is selected as the prior knowledge. Covariance regularization.

[0034] figure ...

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Abstract

The invention discloses a probability linear speaker-distinguishing identifying method based on priori knowledge structured covariance, which is capable of structuring a covariance hypothesis and iterative process of a probability linear identifying-analyzing model based on random useful information related to training voice; and finally, a probability linear identifying-analyzing model that can be more distinctive and can reflect the real situation can be trained; and at the same time, two structuring coefficients are introduced to make the model adjustable and can be self-adaptive to be optimum aiming to various different structuring information. By adopting the model trained by this method provided herein, compared with the traditional model, the evaluating effect of identifying the speaker on the same dataset is improved significantly; and the equal error rate (EER) and the minimum detect error cost function (norm minDCF) can be lowered 10 percent to 20 percent in the evaluating database of identifying an internationally authoritative speaker.

Description

technical field [0001] The invention relates to the field of voiceprint recognition, in particular to a speaker recognition method based on prior knowledge regularization covariance probabilistic linear discrimination analysis. Background technique [0002] Speaker recognition technology is a technology that uses the speaker's characteristic information contained in the speech signal to make a judgment and identify the true identity behind it. Speaker recognition technology has been widely used in identification, video conferencing, access control, military criminal investigation and many other fields, and has developed into an increasingly important modern biometric authentication technology. In recent years, the speaker recognition method based on the total variation factor has become the mainstream method in the field of speaker recognition, which does not strictly distinguish between speakers and channels, and models them as a whole. Through this technology, the first-o...

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Application Information

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IPC IPC(8): G10L17/02G10L17/04
Inventor 李明蔡炜城
Owner SYSU CMU SHUNDE INT JOINT RES INST
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