The invention provides a phonetic
signal feature
processing method of voiceprint identification in a
noise environment, which includes the steps of: (1) carrying out early stage
processing on signals according to a phonetic
signal characteristic, the
processing including
signal pre-emphasis, endpoint detection, and selection of window functions; (2) estimating a fundamental tone period of a sounding individual, carrying out spectrum
smoothing processing on the phonetic signal based on the fundamental tone period, obtaining a new spectrum envelope, calculating the energy passing through a Mel filter, and finally obtaining a Mel
smoothing coefficient (SFCC) through
Discrete Cosine Transform (DCT) calculation; and (3) carrying out post-processing on the SFCC by combination of a mean value reduction method, variance normalization, a
time sequence filter method, and a weight autoregression
moving average filter method, and obtaining a regression balance parameter (MVDA). The purpose is to remove individual sounding unstable factors by
smoothing the spectrum envelope and to remove the ambient
noise influence through a post-processing
algorithm, and the false
identification rate of the voiceprint identification is finally reduced.