Topic
Phrase
About: Phrase is a research topic. Over the lifetime, 12580 publications have been published within this topic receiving 317823 citations. The topic is also known as: syntagma & phrases.
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14 May 2006
TL;DR: A generative statistical model of speech-to-text translation is developed as an extension of existing models of phrase-based text translation that translates speech by mapping ASR word lattices to lattices of phrase sequences.
Abstract: A generative statistical model of speech-to-text translation is developed as an extension of existing models of phrase-based text translation. Speech is translated by mapping ASR word lattices to lattices of phrase sequences which are then translated using operations developed for text translation. Performance is reported on Chinese to English translation of Mandarin Broadcast News.
63 citations
TL;DR: This paper examined some lexico-grammatical features of an introductory geology textbook, particularly the use of grammatical metaphor (Halliday 1985a) and the associated features of verb type, subject-noun phrase, and choice of thematization.
63 citations
Proceedings Article•
15 Feb 2008TL;DR: A cohesion constraint based on a dependency tree for the source sentence allows the decoder to employ arbitrary, non-syntactic phrases, but ensures that those phrases are translated in an order that respects the source tree’s structure.
Abstract: Phrase-based decoding produces state-of-theart translations with no regard for syntax. We add syntax to this process with a cohesion constraint based on a dependency tree for the source sentence. The constraint allows the decoder to employ arbitrary, non-syntactic phrases, but ensures that those phrases are translated in an order that respects the source tree’s structure. In this way, we target the phrasal decoder’s weakness in order modeling, without affecting its strengths. To further increase flexibility, we incorporate cohesion as a decoder feature, creating a soft constraint. The resulting cohesive, phrase-based decoder is shown to produce translations that are preferred over non-cohesive output in both automatic and human evaluations.
63 citations
TL;DR: Infants rely on object labels to guide their inductive inferences only when the labels were presented referentially, embedded within an intentional naming phrase, and marked as count nouns.
Abstract: To clarify the role of labels in early induction, we compared 16-month-old infants' (n = 114) generalization of target properties to test objects when objects were introduced by the experimenter in one of the following ways: (a) with a general attentional phrase, (b) highlighted with a flashlight and a general attentional phrase, (c) via a recorded voice that labeled the objects using a naming phrase, (d) with a label consisting of a count noun embedded within a naming phrase, (e) with a label consisting of a single word that was not marked as belonging to a particular grammatical form class, and (f) with a label consisting of an adjective. Infants relied on object labels to guide their inductive inferences only when the labels were presented referentially, embedded within an intentional naming phrase, and marked as count nouns. These results suggest that infants do not view labels as attributes of objects; rather, infants understand that count-noun labels are intentional markers denoting category membership.
63 citations
29 Jun 2005
TL;DR: In this paper, a semantic role labeling system constructed on top of the full syntactic analysis of text is introduced, surpassing the best system that uses partial syntax by almost 6%.
Abstract: In this paper we introduce a semantic role labeling system constructed on top of the full syntactic analysis of text The labeling problem is modeled using a rich set of lexical, syntactic, and semantic attributes and learned using one-versus-all AdaBoost classifiers
Our results indicate that even a simple approach that assumes that each semantic argument maps into exactly one syntactic phrase obtains encouraging performance, surpassing the best system that uses partial syntax by almost 6%
63 citations