In this paper we present the contents of the University of Amsterdam submission in the CLEF Cross Language Speech Retrieval 2007 English task. We describe the effects of using character n-grams and field combinations on both monolingual English retrieval, and crosslingual Dutch to English retrieval.

We use web-scale N-grams in a base NP parser that correctly analyzes 95.4% of the base NPs in natural text. Web-scale data improves performance. That is, there is no data like more data. Performance scales log-linearly with the number of parameters in the model (the number of unique N-grams). The web-scale N-grams are particularly helpful in harder cases, such as NPs that contain conjunctions.

Character n-grams have been identified as the most successful feature in both singledomain and cross-domain Authorship Attribution (AA), but the reasons for their discriminative value were not fully understood. We identify subgroups of character n-grams that correspond to linguistic aspects commonly claimed to be covered by these features: morphosyntax, thematic content and style. We evaluate t...

This paper presents a Constraint Grammarinspired machine learner and parser, Ling­ Pars, that assigns dependencies to morpho­ logically annotated treebanks in a functioncentred way. The system not only bases at­ tachment probabilities for PoS, case, mood, lemma on those features' function probabili­ ties, but also uses topological features like function/PoS n-grams, barrier tags and daughter-se...

In this paper, a new language model, the Multi-Class Composite N-gram, is proposed to avoid a data sparseness problem in small amount of training data. The Multi-Class Composite Ngram maintains an accurate word prediction capability and reliability for sparse data with a compact model size based on multiple word clusters, so-called Multi-Classes. In the Multi-Class, the statistical connectivity...

In this paper, we propose a system which improves text catchphrases on the web using onomatopoeia and the Japanese Google N-grams. Onomatopoeia is regarded as a fundamental tool in daily communication for people. The proposed system inserts an onomatopoetic word into plain text catchphrases. Being based on a large catchphrase encyclopedia, the proposed system evaluates each catchphrase’s candid...

In this article, we investigate the properties of phoneme N-grams across half of the world's languages. We investigate if the sizes of three different N-gram distributions of the world's language families obey a power law. Further, the N-gram distributions of language families parallel the sizes of the families, which seem to obey a power law distribution. The correlation between N-gram distrib...

In this paper, we propose a method of automatically generating multiple-choice fill-inthe-blank exercises from existing text passages that challenge a reader’s comprehension skills and contextual awareness. We use a unique application of word co-occurrence likelihoods and the Google n-grams corpus to select words with strong contextual links to their surrounding text, and to generate distractor...

In this paper, we extend current state-of-theart research on unsupervised acquisition of scripts, that is, stereotypical and frequently observed sequences of events. We design, evaluate and compare different methods for constructing models for script event prediction: given a partial chain of events in a script, predict other events that are likely to belong to the script. Our work aims to answ...