Code-Switching in End-to-End Automatic Speech Recognition: A Systematic Literature Review

• URL: http://arxiv.org/abs/2507.07741v1
• Date: Thu, 10 Jul 2025 13:21:12 GMT
• Title: Code-Switching in End-to-End Automatic Speech Recognition: A Systematic Literature Review
• Authors: Maha Tufail Agro, Atharva Kulkarni, Karima Kadaoui, Zeerak Talat, Hanan Aldarmaki,
• Abstract summary: We collect and manually annotate papers published in peer reviewed venues.<n>We document the languages considered, datasets, metrics, model choices, and performance.<n>We present a discussion of challenges in end-to-end ASR for code-switching.
• Score: 7.354683587671182
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Motivated by a growing research interest into automatic speech recognition (ASR), and the growing body of work for languages in which code-switching (CS) often occurs, we present a systematic literature review of code-switching in end-to-end ASR models. We collect and manually annotate papers published in peer reviewed venues. We document the languages considered, datasets, metrics, model choices, and performance, and present a discussion of challenges in end-to-end ASR for code-switching. Our analysis thus provides insights on current research efforts and available resources as well as opportunities and gaps to guide future research.

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