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Head (linguistics)

About: Head (linguistics) is a research topic. Over the lifetime, 2540 publications have been published within this topic receiving 29023 citations. The topic is also known as: nucleus.


Papers
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Book ChapterDOI
01 Jan 1999
TL;DR: This paper shows that the problem of prepositional phrase attachment ambiguity is analogous to n-gram language models in speech recognition, and that one of the most common methods for language modeling, the backed-off estimate, is applicable.
Abstract: Recent work has considered corpus-based or statistical approaches to the problem of prepositional phrase attachment ambiguity. Typically, ambiguous verb phrases of the form v np1 p np2 are resolved through a model which considers values of the four head words (v, n1, p and n2). This paper shows that the problem is analogous to n-gram language models in speech recognition, and that one of the most common methods for language modeling, the backed-off estimate, is applicable. Results on Wall Street Journal data of 84.5% accuracy are obtained using this method. A surprising result is the importance of low-count events — ignoring events which occur less than 5 times in training data reduces performance to 81.6%.

207 citations

Proceedings ArticleDOI
20 May 2002
TL;DR: This paper analyzed quantitatively head and facial movements that accompany speech and investigated how they relate to the text's prosodic structure, finding that the direction and strength of head movements vary from one speaker to another, yet their timing is typically well synchronized with the spoken text.
Abstract: As we articulate speech, we usually move the head and exhibit various facial expressions. This visual aspect of speech aids understanding and helps communicating additional information, such as the speaker's mood. We analyze quantitatively head and facial movements that accompany speech and investigate how they relate to the text's prosodic structure. We recorded several hours of speech and measured the locations of the speakers' main facial features as well as their head poses. The text was evaluated with a prosody prediction tool, identifying phrase boundaries and pitch accents. Characteristic for most speakers are simple motion patterns that are repeatedly applied in synchrony with the main prosodic events. Direction and strength of head movements vary widely from one speaker to another, yet their timing is typically well synchronized with the spoken text. Understanding quantitatively the correlations between head movements and spoken text is important for synthesizing photo-realistic talking heads. Talking heads appear much more engaging when they exhibit realistic motion patterns.

201 citations

Journal ArticleDOI
Ur Shlonsky1
01 Dec 2004-Lingua
TL;DR: A phrasal-movement analysis of word order in Hebrew and Arabic noun phrases and develops a configurational theory of agreement, which explains why some adverbials, but not others, may occur inside a derived nominal.

194 citations

Journal ArticleDOI
01 Sep 1980-Language
TL;DR: In this article, a noun's countability preference can be computed by checking its potential for occurrence in a definitive set of countability environments, i.e., whether a noun can be used both countably and uncountably in different NP environments.
Abstract: The customary disjunctive marking of lexical entries for English nouns as [+ countable] does not match the fact that the majority can be used both countably and uncountably in different NP environments: this binary opposition is characteristic not of the nouns, but of the NP's which they head. Nevertheless, nouns do have countability preferences; some enter countable environments more readily than others. And not all nouns occur in all kinds of countability environments. A noun's countability preference can be computed by checking its potential for occurrence in a definitive set of countability environments. In the dialect examined here, wellformedness conditions on NP must consider eight levels of countability among English nouns-not, as custom has it, only two.*

189 citations


Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20222
202168
202090
201986
201890
201790