Modeling the impact of orthographic coding on Czech–Polish and Bulgarian–Russian reading intercomprehension

Abstract

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.

incom.py – A Toolbox for Calculating Linguistic Distances and Asymmetries between Related Languages

“…Both language pairs have similar lexical distances, however, the asymmetric conditional entropy based measures suggest that Czech readers should have more difficulties reading Polish text than vice versa. The asymmetry between Bulgarian and Russian is very small with a predicted minimal advantage for Russian readers (Stenger et al, 2017b). Additionally Stenger et al (2017a) found that word-length normalized adaptation surprisal appears to be a better predictor than aggregated Levenshtein distance when the same stimuli sets in different language pairs are compared.…”

“…While it has been common to use (modifications of) the Levenshtein distance (Levenshtein, 1966) to predict phonetic and orthographic similarity (Beijering et al, 2008;Gooskens, 2007;Vanhove, 2016), this string-edit distance is completely symmetric. To account for asymmetric cross-lingual intelligibility Stenger et al (2017b) employ additional measures of conditional entropy and surprisal (Shannon, 1948). Conditional character adaptation entropy and word adaptation surprisal, as proposed by Stenger et al (2017b), quantify the difficulties humans encounter when mapping one orthographic system to another and reveal asymmetries depending on stimulus-decoder configurations in language pairs.…”

“…RU: the BG participants understand a slightly larger number of the RU words (74.67%) than the RU participants understand the BG words they are presented with (71.33%). This can be explained by the fact that there are only slight differences between the two languages on the graphicorthographical level (for more details see (Stenger et al, 2017b)).…”

“…To account for asymmetric cross-lingual intelligibility Stenger et al (2017b) employ additional measures of conditional entropy and surprisal (Shannon, 1948). Conditional character adaptation entropy and word adaptation surprisal, as proposed by Stenger et al (2017b), quantify the difficulties humans encounter when mapping one orthographic system to another and reveal asymmetries depending on stimulus-decoder configurations in language pairs. Similarly, the research of Jágrová et al (2016) shows that Czech and Polish, both West Slavic, using the Latin script, are orthographically more distant from each other than Bulgarian and Russian, South and East Slavic respectively using the Cyrillic script.…”

Multilingual Learnability and Reaction Time in Online Slavic Intercomprehension Experiments

“…The transparency of vocabularies, along with phonetic, morphological and syntactic structures, is typically asymmetric across Slavic languages (e.g. Jágrová et al 2017;Stenger et al 2017;Golubović 2016).…”