Publications
Tagged As
The MITLL/AFRL IWSLT-2014 MT System
Summary
Summary
This report summarizes the MITLL-AFRL MT and ASR systems and the experiments run using them during the 2014 IWSLT evaluation campaign. Our MT system is much improved over last year, owing to integration of techniques such as PRO and DREM optimization, factored language models, neural network joint model rescoring, multiple...
Using deep belief networks for vector-based speaker recognition
Summary
Summary
Deep belief networks (DBNs) have become a successful approach for acoustic modeling in speech recognition. DBNs exhibit strong approximation properties, improved performance, and are parameter efficient. In this work, we propose methods for applying DBNs to speaker recognition. In contrast to prior work, our approach to DBNs for speaker recognition...
Content+context=classification: examining the roles of social interactions and linguist content in Twitter user classification
Summary
Summary
Twitter users demonstrate many characteristics via their online presence. Connections, community memberships, and communication patterns reveal both idiosyncratic and general properties of users. In addition, the content of tweets can be critical for distinguishing the role and importance of a user. In this work, we explore Twitter user classification using...
VizLinc: integrating information extraction, search, graph analysis, and geo-location for the visual exploration of large data sets
Summary
Summary
In this demo paper we introduce VizLinc; an open-source software suite that integrates automatic information extraction, search, graph analysis, and geo-location for interactive visualization and exploration of large data sets. VizLinc helps users in: 1) understanding the type of information the data set under study might contain, 2) finding patterns...
Exploiting morphological, grammatical, and semantic correlates for improved text difficulty assessment
Summary
Summary
We present a low-resource, language-independent system for text difficulty assessment. We replicate and improve upon a baseline by Shen et al. (2013) on the Interagency Language Roundtable (ILR) scale. Our work demonstrates that the addition of morphological, information theoretic, and language modeling features to a traditional readability baseline greatly benefits...
A new multiple choice comprehension test for MT
Summary
Summary
We present results from a new machine translation comprehension test, similar to those developed in previous work (Jones et al., 2007). This test has documents in four conditions: (1) original English documents; (2) human translations of the documents into Arabic; conditions (3) and (4) are machine translations of the Arabic...
Standardized ILR-based and task-based speech-to-speech MT evaluation
Summary
Summary
This paper describes a new method for task-based speech-to-speech machine translation evaluation, in which tasks are defined and assessed according to independent published standards, both for the military tasks performed and for the foreign language skill levels used. We analyze task success rates and automatic MT evaluation scores (BLEU and...
Development and use of a comprehensive humanitarian assessment tool in post-earthquake Haiti
Summary
Summary
This paper describes a comprehensive humanitarian assessment tool designed and used following the January 2010 Haiti earthquake. The tool was developed under Joint Task Force -- Haiti coordination using indicators of humanitarian needs to support decision making by the United States Government, agencies of the United Nations, and various non-governmental...
Content + context networks for user classification in Twitter
Summary
Summary
Twitter is a massive platform for open communication between diverse groups of people. While traditional media segregates the world's population on lines of language, age, physical location, social status, and many other characteristics, Twitter cuts through these divides. The result is an extremely diverse social network. In this work, we...
The MIT-LL/AFRL IWSLT-2013 MT System
Summary
Summary
This paper describes the MIT-LL/AFRL statistical MT system and the improvements that were developed during the IWSLT 2013 evaluation campaign [1]. As part of these efforts, we experimented with a number of extensions to the standard phrase-based model that improve performance on the Russian to English, Chinese to English, Arabic...