TY - GEN
T1 - Speech Feature Extraction Based on Linear Prediction Residual
AU - Xu, Lu
AU - Liu, Hongjin
AU - Zhang, Shaolin
AU - Wang, Mingjiang
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/23
Y1 - 2020/10/23
N2 - Linear prediction coding (LPC) is the core technology in speech processing, which has been successfully applied in speech recognition, synthesis and coding. LPC coefficient can well represent the speaker's vocal tract information, and is widely used in the field of speaker recognition. However, the epiphytic LPC residual is often ignored. This paper shows that the LPC residual contains information, which can reflect the characteristics of the speaker himself. We extracted new feature parameters (Second moment, third moment) from the LPC residual, combined with LPC coefficients, and input them into a speaker recognition system based on the GRU network. Cross entropy loss is used as a loss function to train the classifier. The experimental results show that the combined parameters effectively improve the system recognition rate by 5% relative to the LPC coefficients.
AB - Linear prediction coding (LPC) is the core technology in speech processing, which has been successfully applied in speech recognition, synthesis and coding. LPC coefficient can well represent the speaker's vocal tract information, and is widely used in the field of speaker recognition. However, the epiphytic LPC residual is often ignored. This paper shows that the LPC residual contains information, which can reflect the characteristics of the speaker himself. We extracted new feature parameters (Second moment, third moment) from the LPC residual, combined with LPC coefficients, and input them into a speaker recognition system based on the GRU network. Cross entropy loss is used as a loss function to train the classifier. The experimental results show that the combined parameters effectively improve the system recognition rate by 5% relative to the LPC coefficients.
KW - Cross Entropy Loss function
KW - GRU
KW - LPC Residual
KW - Speaker Recognition
UR - https://www.scopus.com/pages/publications/85101157041
U2 - 10.1109/ICSIP49896.2020.9339291
DO - 10.1109/ICSIP49896.2020.9339291
M3 - 会议稿件
AN - SCOPUS:85101157041
T3 - 2020 IEEE 5th International Conference on Signal and Image Processing, ICSIP 2020
SP - 768
EP - 772
BT - 2020 IEEE 5th International Conference on Signal and Image Processing, ICSIP 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th IEEE International Conference on Signal and Image Processing, ICSIP 2020
Y2 - 23 October 2020 through 25 October 2020
ER -