Focusing on orthography as a primary linguistic interface in every reading activity, the central research question we address here is how orthographic intelligibility can be measured and predicted between closely related languages. This paper presents methods and findings of modeling orthographic intelligibility in a reading intercomprehension scenario from the information-theoretic perspective. The focus of the study is on two Slavic language pairs: Czech–Polish (West Slavic, using the Latin script) and Bulgarian–Russian (South Slavic and East Slavic, respectively, using the Cyrillic script). In this article, we present computational methods for measuring orthographic distance and orthographic asymmetry by means of the Levenshtein algorithm, conditional entropy and adaptation surprisal method that are expected to predict the influence of orthography on mutual intelligibility in reading.

Researchers on bilingual processing can benefit from computational tools developed in artificial intelligence. We show that a normalized Levenshtein distance function can efficiently and reliably simulate bilingual orthographic similarity ratings. Orthographic similarity distributions of cognates and non-cognates were identified across pairs of six European languages: English, German, French, Spanish, Italian, and Dutch. Semantic equivalence was determined using the conceptual structure of a translation database. By using a similarity threshold, large numbers of cognates could be selected that nearly completely included the stimulus materials of experimental studies. The identified numbers of form-similar and identical cognates correlated highly with branch lengths of phylogenetic language family trees, supporting the usefulness of the new measure for cross-language comparison. The normalized Levenshtein distance function can be considered as a new formal model of cross-language orthographic similarity.

The aim of the present study is twofold. First, it addresses the question of how well Norwegians are able to identify Norwegian dialects. Second, it investigates the role which intonation plays in the identification of Norwegian dialects. In a number of listening experiments, 15 groups of young Norwegians from different parts of Norway were asked to identify 15 different dialects. The dialects were presented in the original form as well as in a version that was manipulated by computer in such a way that the intonation was removed. In this way it was possible to see how important intonation is for the identification of the dialects. The results are put into perspective by comparing them to results of similar experiments with Dutch dialects. Norwegians turned out to be less good at recognizing Norwegian dialects than Dutchmen. Linguistic and extra-linguistic explanations are given. Furthermore the results show that intonation is more important for the identification of Norwegian dialects than for the identification of Dutch dialects.

We generalize a theorem due to Keilson on the approximate exponentiality of waiting times for rare events in regenerative processes. We use the result to investigate the limit distribution for a family of first entrance times in a sequence of Ehrenfest urn models. As a second application, we consider approximate pattern matching, a problem arising in molecular biology and other areas.