Code-Switching in End-to-End Automatic Speech Recognition: A Systematic Literature Review
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915381980954624 |
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| author | Agro, Maha Tufail Kulkarni, Atharva Kadaoui, Karima Talat, Zeerak Aldarmaki, Hanan |
| author_facet | Agro, Maha Tufail Kulkarni, Atharva Kadaoui, Karima Talat, Zeerak Aldarmaki, Hanan |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_07741 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Code-Switching in End-to-End Automatic Speech Recognition: A Systematic Literature Review Agro, Maha Tufail Kulkarni, Atharva Kadaoui, Karima Talat, Zeerak Aldarmaki, Hanan Computation and Language Sound Audio and Speech Processing 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. |
| title | Code-Switching in End-to-End Automatic Speech Recognition: A Systematic Literature Review |
| topic | Computation and Language Sound Audio and Speech Processing |
| url | https://arxiv.org/abs/2507.07741 |