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Damianos Karakos
Researcher at BBN Technologies
Publications - 69
Citations - 1722
Damianos Karakos is an academic researcher from BBN Technologies. The author has contributed to research in topics: Language model & Keyword spotting. The author has an hindex of 20, co-authored 69 publications receiving 1625 citations. Previous affiliations of Damianos Karakos include Raytheon & Johns Hopkins University.
Papers
More filters
Journal ArticleDOI
Directional processing of color images: theory and experimental results
TL;DR: Experimental and comparative results in image filtering show very good performance measures when the error is measured in the L*a*b* space, which is known as a space where equal color differences result in equal distances, and therefore, it is very close to the human perception of colors
Journal ArticleDOI
Generalized multichannel image-filtering structures
Damianos Karakos,Panos Trahanias +1 more
TL;DR: A new filter structure, the directional-distance filters (DDF), is introduced, which combine both VDF and VMF in a novel way and are shown to be robust signal estimators under various noise distributions and compare favorably to other multichannel image processing filters.
Improved Speech-to-Text Translation with the Fisher and Callhome Spanish–English Speech Translation Corpus
TL;DR: The Fisher and Callhome Spanish-English Speech Translation Corpus is introduced, supplementing existing LDC audio and transcripts with ASR 1-best, lattice, and oracle output produced by the Kaldi recognition system and English translations obtained on Amazon’s Mechanical Turk.
Proceedings ArticleDOI
Score normalization and system combination for improved keyword spotting
Damianos Karakos,Richard Schwartz,Stavros Tsakalidis,Le Zhang,Shivesh Ranjan,Tim Ng,Roger Hsiao,Guruprasad Saikumar,Ivan Bulyko,Long Nguyen,John Makhoul,Frantisek Grezl,Mirko Hannemann,Martin Karafiat,Igor Szöke,Karel Vesely,Lori Lamel,Viet Bac Le +17 more
TL;DR: Two techniques are shown to yield improved Keyword Spotting (KWS) performance when using the ATWV/MTWV performance measures, which resulted in the highest performance for the official surprise language evaluation for the IARPA-funded Babel project in April 2013.
Proceedings ArticleDOI
Combining vector median and vector directional filters: the directional-distance filters
Damianos Karakos,Panos Trahanias +1 more
TL;DR: A new class of filters, the directional-distance filters (DDF), which combine both VDF and VMF in a novel way are introduced, which can eliminate the noise much more effectively than the VMF (even the impulsive noise), and that they have the property of chromaticity preservation.