Method and system for voiceprint recognition based on vector quantization based

Abstract

The invention discloses a method and a system for voiceprint recognition based on vector quantization, which have high recognition performance and noise immunity, are effective in recognition, require few modeling data, and are quick in judgment speed and low in complexity. The method includes steps: acquiring audio signals; preprocessing the audio signals; extracting audio signal characteristic parameters by using MFCC (mel-frequency cepstrum coefficient) parameters, wherein the order of the MFCC ranges from 12 to 16; template training, namely using the LBG (linde, buzo and gray) clustering algorithm to set up a codebook for each speaker and store the codebooks in an audio data base to be used as the audio templates of the speakers; voiceprint recognizing, namely comparing acquired characteristic parameters of the audio signals to be recognized with the speaker audio templates set up in the audio data base and judging according to weighting Euclidean distance measure, and if the corresponding speaker template enables the audio characteristic vector X of a speaker to be recognized to have the minimum average distance measure, the speaker is supposed to be recognized.

Description

technical field [0001] The invention belongs to the speech signal processing technology, in particular to a voiceprint recognition method and system based on vector quantization for identifying the speaker's identity by using the speaker's speech signal. Background technique [0002] In recent years, with the wide application of information processing and artificial intelligence technology, and people's urgent requirements for fast and effective identity verification, traditional password authentication has gradually lost its status. In the field of biometrics, speaker-based Voice identification technology has been favored by more and more people. [0003] Due to the physiological differences in the pronunciation organs of each person and the acquired behavioral differences, the pronunciation methods and speaking habits are different, so it is possible to use the speaker's voice to identify the identity. In addition to the advantages of no forgetting, no need to remember, a...

AI Technical Summary

Problems solved by technology

However, the disadvantage is that the speech signal is normally distributed in an ellipse shape, and the distribution of each vector is not equal, and it does not get a good response in the Euclidean distance measurement based on the traditional VQ speaker recognition system.

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