Damianos Karakos (Raytheon BBN) “The Raytheon BBN Cross-lingual Information Retrieval System developed under the IARPA MATERIAL Program”
3400 N. Charles Street
Raytheon BBN participated in the IARPA MATERIAL program, whose objective is to enable rapid development of language-independent methods for cross-lingual information retrieval (CLIR). The challenging CLIR task of retrieving documents written (or spoken) in one language so that they satisfy an information need expressed in a different language is exacerbated by unique challenges posed by the MATERIAL program: limited training data for automatic speech recognition and machine translation, scant lexical resources, non-standardized orthography, etc. Furthermore, the format of the queries and the “Query-Weighted Value” performance measure are non-standard and not previously studied in the IR community. In this talk, we will describe the Raytheon BBN CLIR system, which was successful at addressing the above challenges and unique characteristics of the program.
Damianos Karakos has been at Raytheon BBN for the past nine years, where he is currently a Senior Principal Engineer, Research. Before that, he was research faculty at Johns Hopkins University. He has worked on several Government projects (e.g., DARPA GALE, DARPA RATS, IARPA BABEL, IARPA MATERIAL, IARPA BETTER) and on a variety of HLT-related topics (e.g., speech recognition, speech activity detection, keyword search, information retrieval). He has published more than 60 peer-reviewed papers. His research interests lie at the intersection of human language technology and machine learning, with an emphasis on statistical methods. He obtained a PhD in Electrical Engineering from the University of Maryland, College Park, in 2002.