One of the benefits of language identification that is particularly relevant for code-switching (CS) research is that it permits insight into how the languages are mixed (i.e., the level of integration of the languages). The aim of this paper is to quantify and visualize the nature of the integration of languages in CS documents using simple language-independent metrics that can be adopted by linguists. In our contribution, we (a) make a linguistic case for classifying CS types according to how the languages are integrated; (b) describe our language identification system; (c) introduce an Integration-index (I-index) derived from HMM transition probabilities; (d) employ methods for visualizing integration via a language signature (or switching profile); and (e) illustrate the utility of our simple metrics for linguists as applied to Spanish-English texts of different switching profiles.
Guzmán et al. REF have similar aims, focusing on producing methods for visualizing language integration via a language signature or profile.
Simple Tools for Exploring Variation in Code-switching for Linguists.
CodeSwitch@EMNLP
Computer Science