Are Multilingual Models Effective in Code-Switching?

Understand

Multilingual language models have shown decent performance in multilingual and cross-lingual natural language understanding tasks.

• However, the power of these multilingual models in code-switching tasks has not been fully explored.
• In this paper, we study the effectiveness of multilingual language models to understand their capability and adaptability to the mixed-language setting by considering the inference speed, performance, and number of parameters to measure their practicality.
• We conduct experiments in three language pairs on named entity recognition and part-of-speech tagging and compare them with existing methods, such as using bilingual embeddings and multilingual meta-embeddings.