Gwon, YoungjuneCampbell, William M.Sturim, Douglas E.Kung, H.2017-09-292017-09-29Gwon, Youngjune L., William M. Campbell, Douglas E. Sturim, and H. T. Kung. 2016. "Language Recognition via Sparse Coding." In Proc. Interspeech 2016, pp. 2920-2924.http://nrs.harvard.edu/urn-3:HUL.InstRepos:33973840Spoken language recognition requires a series of signal processing steps and learning algorithms to model distinguishing characteristics of different languages. In this paper, we present a sparse discriminative feature learning framework for language recognition. We use sparse coding, an unsupervised method, to compute efficient representations for spectral features from a speech utterance while learning basis vectors for language models. Differentiated from existing approaches in sparse representation classification, we introduce a maximum a posteriori (MAP) adaptation scheme based on online learning that further optimizes the discriminative quality of sparse-coded speech features. We empirically validate the effectiveness of our approach using the NIST LRE 2015 dataset.en-USConference Paper2017-09-2910.21437/Interspeech.2016-881