Abstract: Speech feature extraction is an important step in the process of voiceprint recognition.There is a large gap between men and women in the distribution of sound frequency,but the existing feature extraction algorithms have not made correspon-ding improvements for the sound frequency characteristics of different genders.To solve the above problems,a speech feature extraction algorithm LFBank designed for female voiceprint recognition is proposed.The linear filter banks is introduced into the feature extraction process,and its linear distribution is used to make up for the deficiency of the traditional Mel filter banks in extracting high-frequency region information.On the other hand,in order to break through the limitation of single gender and broaden the application scenarios,combining the advantages of linear filter banks and Mel filter banks,LFBank and FBank features are combined to obtain mixed feature vectors for voiceprint recognition.The LFBank is compared with the commonly used feature FBank and MFCC,and experimental results show that the feature vector based on linear filter bank has more advantages in recognizing female voice.For mixed features,in the comparison experiment with single features,they can achieve better recognition effect than single features and have a wider range of application scenarios.

Key words: Voiceprint recognition, Feature extraction, Sound frequency, Linear filter banks, Mel filter banks, Mixed feature