Centroid-based exemplar selection of ASL non-manual expressions using multidimensional dynamic time warping and MPEG4 features
Syed, Ali Raza
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Citation (published version)Hernisa Kacorri, Ali Raza Syed, Matt Huenerfauth, Carol Neidle. "Centroid-Based Exemplar Selection of ASL Non-Manual Expressions using Multidimensional Dynamic Time Warping and MPEG4 Features." Proceedings of the Workshop on the Representation and Processing of Sign Languages: Corpus Mining, Language Resources and Evaluation Conference 2016. Workshop on the Representation and Processing of Sign Languages: Corpus Mining, Language Resources and Evaluation Conference 2016. Portorož, Slovenia, 2016-05-28 - 2016-05-28
We investigate a method for selecting recordings of human face and head movements from a sign language corpus to serve as a basis for generating animations of novel sentences of American Sign Language (ASL). Drawing from a collection of recordings that have been categorized into various types of non-manual expressions (NMEs), we define a method for selecting an exemplar recording of a given type using a centroid-based selection procedure, using multivariate dynamic time warping (DTW) as the distance function. Through intra- and inter-signer methods of evaluation, we demonstrate the efficacy of this technique, and we note useful potential for the DTW visualizations generated in this study for linguistic researchers collecting and analyzing sign language corpora.
RightsThis open access paper is available under a Attribution-NonCommercial-NoDerivatives 4.0 International license. Copyright 2016 by the European Language Resources Association