Combining semantic and syntactic structure for language modeling

Structured language models for speech recognition have been shown to remedy the weaknesses of n-gram models. All current structured language models are, however, limited in that they do not take into account dependencies between non-headwords. We show that non-headword dependencies contribute to significantly improved word error rate, and that a data-oriented parsing model trained on semantically and syntactically annotated data can exploit these dependencies. This paper also contains the first DOP model trained by means of a maximum likelihood reestimation procedure, which solves some of the theoretical shortcomings of previous DOP models.Comment: 4 page

Algebraicity of the Appell-Lauricella and Horn hypergeometric functions

We extend Schwarz' list of irreducible algebraic Gauss functions to the four classes of Appell-Lauricella functions in several variables and the 14 complete Horn functions in two variables. This gives an example of a family of functions such that for any number of variables there are infinitely many algebraic functions, namely the Lauricella $F_C$ functions.Comment: 24 pages, 6 tables, 2 figure

An improved parser for data-oriented lexical-functional analysis

We present an LFG-DOP parser which uses fragments from LFG-annotated sentences to parse new sentences. Experiments with the Verbmobil and Homecentre corpora show that (1) Viterbi n best search performs about 100 times faster than Monte Carlo search while both achieve the same accuracy; (2) the DOP hypothesis which states that parse accuracy increases with increasing fragment size is confirmed for LFG-DOP; (3) LFG-DOP's relative frequency estimator performs worse than a discounted frequency estimator; and (4) LFG-DOP significantly outperforms Tree-DOP is evaluated on tree structures only.Comment: 8 page

A classification of the irreducible algebraic A-hypergeometric functions associated to planar point configurations

We consider A-hypergeometric functions associated to normal sets in the plane. We give a classification of all point configurations for which there exists a parameter vector such that the associated hypergeometric function is algebraic. In particular, we show that there are no irreducible algebraic functions if the number of boundary points is sufficiently large and A is not a pyramid.Comment: 24 pages, 8 tables, 13 figure

Data-Oriented Language Processing. An Overview

During the last few years, a new approach to language processing has started to emerge, which has become known under various labels such as "data-oriented parsing", "corpus-based interpretation", and "tree-bank grammar" (cf. van den Berg et al. 1994; Bod 1992-96; Bod et al. 1996a/b; Bonnema 1996; Charniak 1996a/b; Goodman 1996; Kaplan 1996; Rajman 1995a/b; Scha 1990-92; Sekine & Grishman 1995; Sima'an et al. 1994; Sima'an 1995-96; Tugwell 1995). This approach, which we will call "data-oriented processing" or "DOP", embodies the assumption that human language perception and production works with representations of concrete past language experiences, rather than with abstract linguistic rules. The models that instantiate this approach therefore maintain large corpora of linguistic representations of previously occurring utterances. When processing a new input utterance, analyses of this utterance are constructed by combining fragments from the corpus; the occurrence-frequencies of the fragments are used to estimate which analysis is the most probable one. In this paper we give an in-depth discussion of a data-oriented processing model which employs a corpus of labelled phrase-structure trees. Then we review some other models that instantiate the DOP approach. Many of these models also employ labelled phrase-structure trees, but use different criteria for extracting fragments from the corpus or employ different disambiguation strategies (Bod 1996b; Charniak 1996a/b; Goodman 1996; Rajman 1995a/b; Sekine & Grishman 1995; Sima'an 1995-96); other models use richer formalisms for their corpus annotations (van den Berg et al. 1994; Bod et al., 1996a/b; Bonnema 1996; Kaplan 1996; Tugwell 1995).Comment: 34 pages, Postscrip

A Data-Oriented Model of Literary Language

We consider the task of predicting how literary a text is, with a gold standard from human ratings. Aside from a standard bigram baseline, we apply rich syntactic tree fragments, mined from the training set, and a series of hand-picked features. Our model is the first to distinguish degrees of highly and less literary novels using a variety of lexical and syntactic features, and explains 76.0 % of the variation in literary ratings.Comment: To be published in EACL 2017, 11 page

An Examination of body composition measurement methods in children

Introduction . Body-composition methods include underwater weighing (UWW), skinfold thickness (SKF), bioelectrical impedance (BIA), and the BOD POD. Although these techniques are used routinely, each has its inherent limitations, especially in children. Purpose . The purpose of this study was to examine the various methods of body composition in children. Methods . The body composition of 7 boys between the ages of 12-14 (13.1 +/- 1.1 years) was determined using the BOD POD, UWW, SKF, and BIA. Results . Percent body fat estimated from the BOD POD (21.9 +/- 7.8%BF) was not significantly different than the estimated percent fat from UWW (21.8 +/- 7.3%BF). Conclusion . The strong relationship between the BOD POD and UWW in this study suggests that the BOD POD is a valid method of measuring body composition in children