Orthographic and Morphological Correspondences between Related Slavic Languages as a Base for Modeling of Mutual Intelligibility
14819Authors
nan
Abstract
AbstractIn an intercomprehension scenario, typically a native speaker of language L1 is confronted with output from an unknown, but related language L2. In this setting, the degree to which the receiver recognizes the unfamiliar words greatly determines communicative success. Despite exhibiting great string-level differences, cognates may be recognized very successfully if the receiver is aware of regular correspondences which allow to transform the unknown word into its familiar form. Modeling L1-L2 intercomprehension then requires the identification of all the regular correspondences between languages L1 and L2. We here present a set of linguistic orthographic correspondences manually compiled from comparative linguistics literature along with a set of statistically-inferred suggestions for correspondence rules. In order to do statistical inference, we followed the Minimum Description Length principle, which proposes to choose those rules which are most effective at describing the data. Our statistical model was able to reproduce most of our linguistic correspondences (88.5% for Czech-Polish and 75.7% for Bulgarian-Russian) and furthermore allowed to easily identify many more non-trivial correspondences which also cover aspects of morphology.
Keywords
Full Content
Orthographic and Morphological Correspondences between Related Slavic Languages as a Base for Modeling of Mutual Intelligibility Andrea Fischer, Klára Jágrová, Irina Stenger, Tania Avgustinova, Dietrich Klakow, and Roland Marti Saarland University, Collaborative Research Center (SFB) 1102: Information Density and Linguistic Encoding, Campus A 2.2, 66123 Saarbrücken, Germany Project C4: INCOMSLAV – Mutual Intelligibility and Surprisal in Slavic Intercomprehension {kjagrova, avgustinova}@coli.uni- saarland.de {ira.stenger, rwmslav}@mx.uni- saarland.de {andrea.fischer, dietrich.klakow}@lsv.uni- saarland.de http://www.sfb1102.uni-saarland.de Abstract In an intercomprehension scenario, typically a native speaker of language L1 is confronted with output from an unknown, but related language L2. In this setting, the degree to which the receiver recognizes the unfamiliar words greatly determines communicative success. Despite exhibiting great string-level differences, cognates may be recognized very successfully if the receiver is aware of regular correspondences which allow to transform the unknown word into its familiar form. Modeling L1-L2 intercomprehension then requires the identification of all the regular correspondences between languages L1 and L2. We here present a set of linguistic orthographic correspondences manually compiled from comparative linguistics literature along with a set of statistically-inferred suggestions for correspondence rules. In order to do statistical inference, we followed the Minimum Description Length principle, which proposes to choose those rules which are most effective at describing the data. Our statistical model was able to reproduce most of our linguistic correspondences (88.5% for Czech-Polish and 75.7% for Bulgarian-Russian) and furthermore allowed to easily identify many more non-trivial correspondences which also cover aspects of morphology. Keywords: comparative linguistics, Minimum Description Length, receptive multilingualism 1. Introduction Similarities in phonology, morphology, syntax and basic vocabulary among Slavic languages are striking, and the possibility of mutual intercomprehension within the Slavic language family is a generally accepted hypothesis. How- ever, similarities and differences must be studied from dif- ferent linguistic perspectives: orthography, morphology, syntax, and lexis. In the present work, we focus on ortho- graphic and morphological relations in two language pairs that we consider representative for the Slavic language fam- ily: Czech and Polish (CS-PL) and Bulgarian and Russian (BG-RU). Czech and Polish are both West Slavic languages that use the Latin alphabet, but differ in their use of digraphs and diacritical signs. Russian and Bulgarian are East and South-East Slavic, respectively, and both use the Cyrillic alphabet. Our hypothesis is that both orthography and morphology are linguistic determinants of mutual intelligibility which may facilitate or impede intercomprehension. Thus, we need to analyze the most frequent orthographic and morphological correspondences in order to uncover systematic similarities and differences between the two language pairs. We analyzed lists of cognates in a previous experiment, in- vestigating the statistical significance of rules formulated on the basis of comparative historical linguistics literature. This revealed that proceeding purely on the basis of know- ledge from comparative linguistics did not give us all nece- ssary rules – many occurring correspondences were miss- ing. In the present contribution, we discuss missing correspon- dences and turn our attention to the statistical inference of correspondence rules. Specifically, we use the Minimum Description Length principle (Grünwald, …
Content truncated to 500 words
Labeled Text
AbstractIn an intercomprehension scenario, typically a native speaker of language L1 is confronted with output from an unknown, but related language L2. In this setting, the degree to which the receiver recognizes the unfamiliar words greatly determines communicative success. Despite exhibiting great string-level differences, cognates may be recognized very successfully if the receiver is aware of regular correspondences which allow to transform the unknown word into its familiar form. Modeling L1-L2 intercomprehension then requires the identification of all the regular correspondences between languages L1 and L2. We here present a set of linguistic orthographic correspondences manually compiled from comparative linguistics literature along with a set of statistically-inferred suggestions for correspondence rules. In order to do statistical inference, we followed the Minimum Description Length principle, which proposes to choose those rules which are most effective at describing the data. Our statistical model was able to reproduce most of our linguistic correspondences (88.5% for Czech-Polish and 75.7% for Bulgarian-Russian) and furthermore allowed to easily identify many more non-trivial correspondences which also cover aspects of morphology.
Publication Details
- Paper ID:
- 14819
- Year:
- 2016
- Publication:
- TIPSTER
- Publication Type:
- conf
- DOI:
- nan