{"ID":2896126,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.07741","arxiv_id":"2507.07741","title":"Code-Switching in End-to-End Automatic Speech Recognition: A Systematic Literature Review","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.","short_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...","url_abs":"https://arxiv.org/abs/2507.07741","url_pdf":"https://arxiv.org/pdf/2507.07741v1","authors":"[\"Maha Tufail Agro\",\"Atharva Kulkarni\",\"Karima Kadaoui\",\"Zeerak Talat\",\"Hanan Aldarmaki\"]","published":"2025-07-10T13:21:12Z","proceeding":"cs.CL","tasks":"[\"cs.CL\",\"cs.SD\",\"eess.AS\"]","methods":"[]","has_code":false}