Training language models for Code-mixed (CM) language is known to be a difficult problem
because of lack of data compounded by the increased confusability due to the presence of …

Abstract Language modeling is the technique to estimate the probability of a sequence of
words. A bilingual language model is expected to model the sequential dependency for …

This work focuses on building language models (LMs) for code-switched text. We propose
two techniques that significantly improve these LMs: 1) A novel recurrent neural network unit …

Curriculum learning strategies are known to improve the accuracy, robustness and
convergence rate for various language learning tasks using deep architectures (Bengio et …

In this work, we present a simple and elegant approach to language modeling for bilingual
code-switched text. Since code-switching is a blend of two or more different languages, a …

Code-switching language modeling is challenging due to statistics of each individual
language, as well as statistics of cross-lingual language are insufficient. To compensate for …

This paper considers the recognition of a widely observed type of bilingual code-switched
speech: the speaker speaks primarily the host language (usually his native language), but …