11-07-2023 дата публикации
Номер: CN116416997A
Принадлежит:
The invention discloses an attention mechanism-based intelligent voice forgery attack detection method, which comprises the following steps of: converting a voice sample from a time domain to a frequency domain for analysis, considering the influence of different filters on feature expression, filtering a frequency spectrum by using various filters, extracting a logarithmic power spectrum and a Mel-frequency cepstral coefficient, and extracting a voice forgery attack from the logarithmic power spectrum and the Mel-frequency cepstral coefficient; three different voice sample voiceprint features of a linear frequency cepstrum coefficient; training a forged voice attack detection model based on an attention mechanism and a residual network, performing adaptive feature selection by using the attention mechanism, enhancing discriminative effective features, suppressing noise and redundant features, and then performing advanced feature extraction and learning through the residual network; and ...
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