CLLGMLMar 25, 2019

A Survey of Code-switched Speech and Language Processing

arXiv:1904.00784v3155 citations
Originality Synthesis-oriented
AI Analysis

It addresses the need for building intelligent systems in multilingual communities, but is incremental as it synthesizes existing research.

This survey reviews computational approaches for processing code-switched speech and natural language, highlighting the scarcity of data and resources while listing available datasets and applications.

Code-switching, the alternation of languages within a conversation or utterance, is a common communicative phenomenon that occurs in multilingual communities across the world. This survey reviews computational approaches for code-switched Speech and Natural Language Processing. We motivate why processing code-switched text and speech is essential for building intelligent agents and systems that interact with users in multilingual communities. As code-switching data and resources are scarce, we list what is available in various code-switched language pairs with the language processing tasks they can be used for. We review code-switching research in various Speech and NLP applications, including language processing tools and end-to-end systems. We conclude with future directions and open problems in the field.

Foundations

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