Infant-directed speech (IDS) is thought to play a key role in determining infant language acquisition. It is thus important to describe how computational models of infant language acquisition behave when given an input of IDS, as compared to adult-directed speech (ADS). In this paper, we explore how an acoustic motif discovery algorithm fares when presented with speech from both registers. Resu...

The task of Semantic Role Labeling (SRL) is often divided into two sub-tasks: verb argument identification, and argument classification. Current SRL algorithms show lower results on the identification sub-task. Moreover, most SRL algorithms are supervised, relying on large amounts of manually created data. In this paper we present an unsupervised algorithm for identifying verb arguments, where ...

We present greedy unsymmetric collocation schemes for solving linear elliptic partial differential equations using radial basis functions. The proposed approach circumvents the ill-conditioning problem associated with the standard collocation technique and enables the efficient solution of problems requiring a large set of collocation points. Numerical studies indicate that the accuracy of gree...

This study examines how different dimensions of corpus frequency data may affect the outcome of statistical modeling of lexical items. The corpus used in our analysis is an elderly speaker corpus in its early development, and the target words are temporal expressions, which might reveal how the speech produced by the elderly is organized. We conduct divisive hierarchical clustering based on two...

Keywords: Volterra integro-differential equations Multistep collocation Superconvergence Stability a b s t r a c t Multistep collocation methods for Volterra integro-differential equations are derived and analyzed. They increase the order of convergence of classical one-step collocation methods, at the same computational cost. The numerical stability analysis is carried out and classes of A 0-s...

In this paper, collocation methods are used for detecting blow-up solutions of nonlinear homogeneous Volterra-Hammerstein integral equations. To do this, we introduce the concept of “blow-up collocation solution” and analyze numerically some blow-up time estimates using collocation methods in particular examples where previous results about existence and uniqueness can be applied. Finally, we d...

The study of translation by bilingual female students studying Arabic had not received much attention, especially with regard to the cultural errors that these made during English-Arabic translations, which resulted in them making mistakes translation. This prompted researchers focus on this area. main objective article is explore common collocation among Federal College Education (Technical), ...

A method is presented for segmenting documents into conceptually related areas. Determining the equivalence of text is often based on the number of word repetitions. This approach is unsuitable for detecting short segments because terms tend not to be repeated across just a few sentences. In this paper we investigate the contribution of two other lexical features to find related words: collocat...

MuLLinG is a model for knowledge extraction (especially lexical extraction from corpora), based on multilevel graphs. Its aim is to allow large-scale data acquisition, by making it easy to realize automatically, and simple to configure by linguists with limited knowledge in computer programming. In MuLLinG, each new level represents the information in a different manner (more and more abstract)...

In this paper, we propose a novel approach for detecting cussing-related offensive content in Twitter. Our approach exploits the lexical collocation of swearing language via statistical topic modeling on a huge Twitter corpus and detects offensive tweets with automatically generated features under a machine learning framework. Our approach performed stably and competitively under a variety of m...