TY - JOUR
T1 - Speaking Style Recognition of Pilots in Flight
AU - Xie, Xiang
AU - Tang, Gang
AU - Xiao, Ze Ping
AU - Li, Tong
N1 - Publisher Copyright:
© 2017, Editorial Department of Transaction of Beijing Institute of Technology. All right reserved.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - The pilots have various speaking styles in flight, such as emotional dialogue, speaking fast and slowly, speaking loudly and quietly, etc. Moreover, the physical and mental pressure of the pilots in flight can cause dialogue speech aberrance. If the speech was processed directly by the traditional speaker recognition system or a speech recognition system without any processing function, the speech performance will be poor. Therefore, the recognition of the pilots' speaking styles, a kind of paralinguistic information, was investigated to assist the subsequent speech recognition system and speaker recognition system. In the study, 6925 samples were collected in the experiment database, 384-dimension acoustic features were extracted, and compared the classification ability of SVMs with different Kernel functions. The experiment results indicated that the SVM with Gauss radial basis Kernel function shows the best performance and its accuracy can reach 91.62%.
AB - The pilots have various speaking styles in flight, such as emotional dialogue, speaking fast and slowly, speaking loudly and quietly, etc. Moreover, the physical and mental pressure of the pilots in flight can cause dialogue speech aberrance. If the speech was processed directly by the traditional speaker recognition system or a speech recognition system without any processing function, the speech performance will be poor. Therefore, the recognition of the pilots' speaking styles, a kind of paralinguistic information, was investigated to assist the subsequent speech recognition system and speaker recognition system. In the study, 6925 samples were collected in the experiment database, 384-dimension acoustic features were extracted, and compared the classification ability of SVMs with different Kernel functions. The experiment results indicated that the SVM with Gauss radial basis Kernel function shows the best performance and its accuracy can reach 91.62%.
KW - Computation paralinguistic
KW - Speaking style recognition
KW - Speech signal
UR - http://www.scopus.com/inward/record.url?scp=85031110785&partnerID=8YFLogxK
U2 - 10.15918/j.tbit1001-0645.2017.07.016
DO - 10.15918/j.tbit1001-0645.2017.07.016
M3 - Article
AN - SCOPUS:85031110785
SN - 1001-0645
VL - 37
SP - 744
EP - 747
JO - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
JF - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
IS - 7
ER -