Brian Delaney

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This paper describes the MIT-LL/AFRL statistical MT system and the improvements that were developed during the IWSLT 2008 evaluation campaign. As part of these efforts, we experimented with a number of extensions to the standard phrase-based model that improve performance for both text and speech-based translation on Chinese and Arabic translation tasks. We(More)
recommendations are those of the authors and are not necessarily endorsed by the United States Government. Abstract—In this paper, we describe our approach and initial results on modeling, detection, and tracking of terrorist groups and their intents based on multimedia data [Popp 2006]. While research on automated information extraction from multimedia(More)
This work describes the optimization of a signal processing front-end for a distributed speech recognition system with the goal of reducing power consumption. Two categories of source code optimizations were used, architectural and algorithmic. Architectural optimizations reduce the power consumption for a particular system , in this case, the HP Labs(More)
We apply statistical relational learning to a database of criminal and terrorist activity to predict attributes and event outcomes. The database stems from a collection of news articles and court records which are carefully annotated with a variety of variables, including categorical and continuous fields. Manual analysis of this data can help inform(More)
The MIT-LL/AFRL MT system implements a standard phrase-based, statistical translation model. It incorporates a number of extensions that improve performance for speech-based translation. During this evaluation our efforts focused on the rapid porting of our SMT system to a new language (Arabic) and novel approaches to translation from speech input. This(More)
low-power, distributed speech recognition, wireless The use of a voice-user interface for mobile wireless devices has been an area of interest for some time. However, these devices are generally limited by computation, memory, and battery energy, so performing high quality speech recognition on an embedded device is a difficult challenge. In this paper, we(More)
In this paper we describe an efficient implementation of a graph search algorithm for phrase-based statistical machine translation. Our goal was to create a decoder that could be used for both our research system and a real-time speech-to-speech machine translation demonstration system. The search algorithm is based on a Viterbi graph search with an A*(More)
This paper describes the MIT-LL/AFRL statistical MT system and the improvements that were developed during the IWSLT 2009 evaluation campaign. As part of these efforts, we experimented with a number of extensions to the standard phrase-based model that improve performance on the Arabic and Turkish to English translation tasks. We discuss the architecture of(More)