Title
Unsupervised Validity Measures for Vocalization Clustering
Grant Title
Dr. Dolittle Project: A Framework for Classification and Understanding of Animal Vocalizations
Document Type
Conference Proceeding
Publication Date
4-2008
Source Publication
IEEE International Conference on Acoustics, Speech and Signal Processing, 2008: ICASSP; Las Vegas, NV, March 31, 2008 - April 4, 2008
Source ISSN
1520-6149
Abstract
This paper describes unsupervised speech/speaker cluster validity measures based on a dissimilarity metric, for the purpose of estimating the number of clusters in a speech data set as well as assessing the consistency of the clustering procedure. The number of clusters is estimated by minimizing the cross-data dissimilarity values, while algorithm consistency is evaluated by calculating the dissimilarity values across multiple experimental runs. The method is demonstrated on the task of Beluga whale vocalization clustering.
Recommended Citation
Kuntoro, C. Adi; Sonstrom, Kristine E.; Scheifele, Peter; and Johnson, Michael T., "Unsupervised Validity Measures for Vocalization Clustering" (2008). Dr. Dolittle Project: A Framework for Classification and Understanding of Animal Vocalizations. 1.
https://epublications.marquette.edu/data_drdolittle/1
Document Rights and Citation of Original
Paper presented at the International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2008, Las Vegas, NV, March 31, 2008 - April 4, 2008. DOI.