Nancy Yu Song, Jérôme Nicon, Biao Min, Ray CC Cheung, Md Ashraful Amin, Hong Yan
2013 International Conference on Machine Learning and Cybernetics
IEEE, Vol. 3, pp. 1218–1223
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.