Speaker recognition method based on multi-coordinate sequence kernel and system thereof

A speaker recognition and multi-coordinate system technology, applied in the field of speaker recognition of the support vector machine model, can solve the problems of no information and unbalanced SVM, so as to reduce computational complexity, improve accuracy and recognition speed effect

Inactive Publication Date: 2010-02-03
TSINGHUA UNIV
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Problems solved by technology

However, the GMM-SVM system does not solve the following two problems: 1) it does not use the information implied by the high-order statistics of the feature sequence; 2) it does not solve the "imbalance" of each dimension of the input space vector of SVM

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  • Speaker recognition method based on multi-coordinate sequence kernel and system thereof
  • Speaker recognition method based on multi-coordinate sequence kernel and system thereof
  • Speaker recognition method based on multi-coordinate sequence kernel and system thereof

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Embodiment Construction

[0044] Embodiments of the invention are described in detail below, examples of which are illustrated in the accompanying drawings. It should be understood that the embodiments described below by referring to the figures are exemplary only for explaining the present invention, and should not be construed as limiting the present invention.

[0045] Such as figure 2 As shown, it is a flow chart of the speaker recognition method based on the support vector machine model of the multi-coordinate sequence kernel of the embodiment of the present invention. The modeling method of the present invention can be implemented in the digital integrated circuit chip according to the following steps. The embodiment of the present invention The recognition method consists of two stages: the training stage and the recognition stage.

[0046] Training phase:

[0047] Step S201, preprocessing the training speech data.

[0048] Wherein, preprocessing the training voice data includes the followin...

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Abstract

The invention provides a speaker recognition method based on a multi-coordinate sequence kernel, comprising a training stage and a recognition stage. The method comprises the following steps: in the training stage, preprocessing training voice; extracting a characteristic vector sequence from the preprocessed training voice; selecting an origin of a multi-coordinate system in a characteristic vector space, and mapping the characteristic vector sequence in each coordinate system; selecting an algorithm according to the coordinate system and splicing the vector sequence of each coordinate systeminto a super-vector; determining a super-vector space and a kernel function of a support vector machine (SVM), and training with the SVM algorithm to obtain a trained speaker model; and in the recognition stage, testing the super-vector by the trained model and outputting a decision mark. In the invention, by effective modeling on the voice signal characteristic sequence, the speaker recognitionmethod helps utilize the information contained in high dimensional statistics, reduce computational complexity of an integrated circuit, and improve speaker recognition accuracy and recognition speed.

Description

technical field [0001] The invention relates to the technical fields of speech recognition and pattern recognition, in particular to a speaker recognition method and system based on a support vector machine model of a multi-coordinate sequence kernel. Background technique [0002] Speaker recognition refers to the technology of using machines to determine the identity of the speaker of a given speech signal. According to different recognition tasks, speaker recognition can be divided into two types: speaker confirmation and speaker identification. Speaker confirmation is to judge whether a given voice comes from a given speaker; speaker identification is to use a given voice to find a given speaker in the test library. Speaker recognition technology is mainly used in systems such as security services and humanized services. [0003] Such as figure 1 As shown, it is a basic flowchart of the speaker recognition system based on the spectrum layer in the prior art, including ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G10L17/00G10L15/08G10L17/04G10L17/08
Inventor 何亮邓妍刘加
Owner TSINGHUA UNIV
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