TY - GEN
T1 - Noise filtering and occurrence identification of mouse ultrasonic vocalization call
AU - Song, Nancy Yu
AU - Nicon, Jérôme
AU - Min, Biao
AU - Cheung, Ray C. C.
AU - Amin, Md Ashraful
AU - Yan, Hong
PY - 2013
Y1 - 2013
N2 - Currently, there exists a large amount of mouse ultrasonic vocalization data to be analyzed. However, manual annotation of mouse ultrasonic vocalization data requires a lot of human efforts and sometimes it is a mission impossible. As a result, a method is proposed in this paper to filter out the noise in the vocalization recordings and automatically identify the occurrence of mouse vocalization calls. The method can speed up the process of annotating the vocalization data.
AB - Currently, there exists a large amount of mouse ultrasonic vocalization data to be analyzed. However, manual annotation of mouse ultrasonic vocalization data requires a lot of human efforts and sometimes it is a mission impossible. As a result, a method is proposed in this paper to filter out the noise in the vocalization recordings and automatically identify the occurrence of mouse vocalization calls. The method can speed up the process of annotating the vocalization data.
KW - Denoise
KW - Mouse ultrasonic vocalization
KW - Mouse Voice Activity Detection
KW - Occurrence detection
KW - Spectral Subtraction
UR - https://www.scopus.com/pages/publications/84907276298
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84907276298&origin=recordpage
U2 - 10.1109/ICMLC.2013.6890775
DO - 10.1109/ICMLC.2013.6890775
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781479902576
VL - 3
SP - 1218
EP - 1223
BT - Proceedings - International Conference on Machine Learning and Cybernetics
PB - IEEE Computer Society
T2 - 12th International Conference on Machine Learning and Cybernetics, ICMLC 2013
Y2 - 14 July 2013 through 17 July 2013
ER -