HMM voiceprint recognition signing-in method and system based on grouping statistics

Abstract

The invention provides an HMM voiceprint recognition signing-in method and system based on grouping statistics. According to the method, at first, a signing-in client side collects voiceprint signals of signers, pre-emphasis, framing, windowing and end point detecting are sequentially carried out on the voiceprint signals, the voiceprint signals are transmitted to a server through a network, and then a signing-in server side carries out voiceprint characteristic parameter extraction on the voiceprint signals to generate signer grouping characteristic parameters and generate grouping characteristic parameters of a grouping model; According to the grouping characteristic parameters of each group of the grouping model and the grouping characteristic parameters of signer voiceprints, whether the signers are members of a certain group is judged; finally, the voiceprints of the signers are judged. According to the method, under the circumstance that the number of the signers is large, real-time efficient voiceprint recognition signing is achieved, investment on public equipment is reduced, use is convenient and efficient, by means of the combination of the system and the method, voiceprint recognition signing is achieved with high recognition efficiency and high real-time property.

Description

technical field [0001] The present invention relates to the technical field of voiceprint recognition, and more specifically, to a method and system for HMM voiceprint recognition sign-in based on group statistics. Background technique [0002] To implement voiceprint recognition and sign-in in an embedded operating system, it is usually necessary to preprocess the input voiceprint, transmit the data to the server, and then generate a voiceprint model, pattern matching, and finally output and record the results. Among them, the voiceprint model refers to two parameters (B, π) of the Hidden Markov Model (HMM), and the training of the model adopts the Baum_Welch algorithm. Generally, a λ=(A, B, π) triplet can be used to succinctly represent a Hidden Markov Model. Hidden Markov models are actually extensions of standard Markov models, adding sets of observable states and probabilistic relationships between those states and hidden states. Pattern matching usually adopts Viterb...

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Problems solved by technology

[0004] The primary purpose of the present invention is to overcome the defects of poor recognition efficiency and real-time performance described in the above-mentioned prior art, and provide a HMM voiceprint recognition and sign-in method based on group statistics with high recognition efficiency and real-time performance

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