Speaker gender automatic recognition method and system based on deep self-coding network
A self-encoding network, automatic identification technology, applied in the field of speaker gender automatic identification methods and systems, to achieve the effect of improving accuracy, reducing computational complexity, and reducing complexity
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[0053] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.
[0054] The invention provides a speaker gender recognition method based on i-vector and deep self-encoding network. In the training phase, the speech signal of the training set is first preprocessed and Mel cepstral coefficient feature extraction is performed, and then a large amount of speech data unrelated to specific speakers and channels is used to train the UBM general background model; based on this UBM and the Mel cepstrum coefficient of a specific speaker Feature extraction i-vector; use the extracted i-vector to train a deep autoencoder network to achieve binary classification of men and women. In the test phase, ...
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