Unsupervised learning of acoustic events using dynamic time warping and hierarchical K-means++ clustering

J. Schmalenstroeer, M. Bartek, R. Haeb-Umbach, in: Interspeech 2011, 2011.

Conference Paper | English
Abstract
In this paper we propose to jointly consider Segmental Dynamic Time Warping and distance clustering for the unsupervised learning of acoustic events. As a result, the computational complexity increases only linearly with the dababase size compared to a quadratic increase in a sequential setup, where all pairwise SDTW distances between segments are computed prior to clustering. Further, we discuss options for seed value selection for clustering and show that drawing seeds with a probability proportional to the distance from the already drawn seeds, known as K-means++ clustering, results in a significantly higher probability of finding representatives of each of the underlying classes, compared to the commonly used draws from a uniform distribution. Experiments are performed on an acoustic event classification and an isolated digit recognition task, where on the latter the final word accuracy approaches that of supervised training.
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Interspeech 2011
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Schmalenstroeer J, Bartek M, Haeb-Umbach R. Unsupervised learning of acoustic events using dynamic time warping and hierarchical K-means++ clustering. In: Interspeech 2011. ; 2011.
Schmalenstroeer, J., Bartek, M., & Haeb-Umbach, R. (2011). Unsupervised learning of acoustic events using dynamic time warping and hierarchical K-means++ clustering. In Interspeech 2011.
@inproceedings{Schmalenstroeer_Bartek_Haeb-Umbach_2011, title={Unsupervised learning of acoustic events using dynamic time warping and hierarchical K-means++ clustering}, booktitle={Interspeech 2011}, author={Schmalenstroeer, Joerg and Bartek, Markus and Haeb-Umbach, Reinhold}, year={2011} }
Schmalenstroeer, Joerg, Markus Bartek, and Reinhold Haeb-Umbach. “Unsupervised Learning of Acoustic Events Using Dynamic Time Warping and Hierarchical K-Means++ Clustering.” In Interspeech 2011, 2011.
J. Schmalenstroeer, M. Bartek, and R. Haeb-Umbach, “Unsupervised learning of acoustic events using dynamic time warping and hierarchical K-means++ clustering,” in Interspeech 2011, 2011.
Schmalenstroeer, Joerg, et al. “Unsupervised Learning of Acoustic Events Using Dynamic Time Warping and Hierarchical K-Means++ Clustering.” Interspeech 2011, 2011.

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