作者：
Lo, Chi-KiuWu, DekaiHKUST
Human Language Technology Center Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong
We present an unsupervised approach to estimate the appropriate degree of contribution of each semantic role type for semantic translation evaluation, yielding a semantic MT evaluation metric whose correlation with hu...
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In this paper, a professional integrated operating system performance measurement system is proposed, designed, and implemented in order to monitor processes and threads. Because monitoring itself is not enough, so th...
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Play Fairal gorithm has been enhanced in various ways. One of the methods is to increase the confusion rates by transforming the algorithm into 3D-playfair which has four tables of 4×4 and accepts trigraph rather...
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This paper describes the submission of Johns Hopkins University for the shared translation task of ACL 2016 First Conference on Machine Translation (WMT 2016). We set up phrase-based, hierarchical phrase-based and syn...
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We describe a method for automatically learning a parser from labeled, bracketed corpora that results in a fast, robust, lightweight parser that is suitable for real-time dialog systems and similar applications. Unlik...
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In this paper, we propose novel structured language modeling methods for code mixing speech recognition by incorporating a well-known syntactic constraint for switching code, namely the Functional Head Constraint (FHC...
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In this paper, we describe the system designed for the TREC 2017 Precision Medicine track by the University of Texas at Dallas (UTD) humanlanguage Technology Research Institute (HLTRI). Our system incorporates an asp...
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We examine how the recently explored class of linear transductions relates to finite-state models. Linear transductions have been neglected historically, but gainined recent interest in statistical machine translation...
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We examine how the recently explored class of linear transductions relates to finite-state models. Linear transductions have been neglected historically, but gainined recent interest in statistical machine translation modeling, due to empirical studies demonstrating that their attractive balance of generative capacity and complexity characteristics lead to improved accuracy and speed in learning alignment and translation models. Such work has until now characterized the class of linear transductions in terms of either (a) linear inversion transduction grammars (LITGs) which are linearized restrictions of inversion transduction grammars or (b) linear transduction grammars (LTGs) which are bilingualized generalizations of linear grammars. In this paper, we offer a new alternative characterization of linear transductions, as relating four finite-state languages to each other. We introduce the devices of zipper finite-state automata (ZFSAs) and zipper finite-state transducers (ZFSTs) in order to construct the bridge between linear transductions and finite-state models.
Lexical chains between two concepts are sequences of semantically related words interconnected via semantic relations. This paper presents a new approach for the automatic construction of lexical chains on knowledge b...
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Zara the Supergirl is an interactive system that, while having a conversation with a user, uses its built in sentiment analysis, emotion recognition, facial and speech recognition modules, to exhibit the human-like re...
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