Dual Language Models for Code Switched Speech Recognition

Understand

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 standard bilingual language model can be improved upon by using structures of the monolingual language models.
• We propose a novel technique called dual language models, which involves building two complementary monolingual language models and combining them using a probabilistic model for switching between the two.
• We evaluate the efficacy of our approach using a conversational Mandarin-English speech corpus.