Description: 在MATLAB环境下实现基于矢量量化的说话人识别系统。在实时录音的情况下，利用该语音识别系统，对不同的人的语音进行辨识。实现与文本无关的自动说话人确认的实时识别。-In the MATLAB environment VQ-based Speaker Recognition System. In real-time recording, the use of the voice recognition system, for different people to carry out voice recognition. Implementation of automatic text-independent speaker verification of real-time identification. Platform: |
Size: 36864 |
Author:candy |
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Description: 说话人识别和确认系统，采用matlab进行编写，能够进行说话人的识别和确认，研究声纹识别很好的参考代码-Speaker identification and verification system that uses matlab to write, to carry out the speaker' s identification and confirmation of a good reference voiceprint identification code Platform: |
Size: 228352 |
Author:smart |
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Description: Finally, probability analysis, based on the chosen database, is performed and
judgment whether the person is recognized is pronounced. Two different modeling
techniques can be suggested for purposes of person identification or verification. The
approach based on Hidden Markov Speaker Models (HMMs) with the mixtures of
Gaussian distribution is text-dependent one. For this technology a speaker is
described by a set of HMMs, constructing the set of speech groups spoken by that
person. The speech groups may be phonemes or words [7]. The text-independent
technology is rested upon Gaussian Mixture Speaker Models. For this technology
each speaker is defined by only one model describing all utterances of that person.
Identification in the range of both approaches is executed by evaluation of maximum
a posteriori probability [7]. Platform: |
Size: 3019776 |
Author:rasul |
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Description: Speech processing applications such as speech enhancement and speaker identification rely on the estimation of relevant parameters from the speech signal. These
parameters must often be estimated from noisy observations since speech signals are
rarely obtained in ‘clean’ acoustic environments in the real world. As a result, the
parameter estimation algorithms we employ must be robust to environmental factors
such as additive noise and reverberation. In this work we derive and evaluate approximate Bayesian algorithms for the following speech processing tasks: 1) speech
enhancement 2) speaker identification 3) speaker verification and 4) voice activity
detection. Platform: |
Size: 1728512 |
Author:an mchol |
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Search - Speaker Verification Identification