# Building a Unified Code-Switching ASR System for South African Languages

arXiv: https://arxiv.org/abs/1807.10949 · HTML: https://mlsanity.com/paper/1807.10949/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Jul 2018.

## Built on by (most cited first, 12 of 12)

- [The Decades Progress on Code-Switching Research in NLP: A Systematic Survey on Trends and Challenges](https://mlsanity.com/paper/2212.09660/) (2022)
- [End-to-End Speech Translation for Code Switched Speech](https://mlsanity.com/paper/2204.05076/) (2022)
- [Investigations on Speech Recognition Systems for Low-Resource Dialectal Arabic-English Code-Switching Speech](https://mlsanity.com/paper/2108.12881/) (2021)
- [Afrispeech-Dialog: A Benchmark Dataset for Spontaneous English Conversations in Healthcare and Beyond](https://mlsanity.com/paper/2502.03945/) (2025)
- [Adapting the adapters for code-switching in multilingual ASR](https://mlsanity.com/paper/2310.07423/) (2023)
- [Code-Switching in End-to-End Automatic Speech Recognition: A Systematic Literature Review](https://mlsanity.com/paper/2507.07741/) (2025)
- [Unified Modeling of Multi-Domain Multi-Device ASR Systems](https://mlsanity.com/paper/2205.06655/) (2022)
- [Phonemic Representation and Transcription for Speech to Text Applications for Under-resourced Indigenous African Languages: The Case of Kiswahili](https://mlsanity.com/paper/2210.16537/) (2022)
- [AsyncSwitch: Asynchronous Text-Speech Adaptation for Code-Switched ASR](https://mlsanity.com/paper/2506.14190/) (2025)
- [Methods of Automatic Matrix Language Determination for Code-Switched Speech](https://mlsanity.com/paper/2410.02521/) (2024)
- [From Monolingual to Multilingual: Evaluating Mamba for ASR in South African Languages](https://mlsanity.com/paper/2607.01502/) (2026)
- [AfriSwitch: A Benchmark for In-the-Wild African Code-Switched Speech Recognition](https://mlsanity.com/paper/2608.26434/) (2026)

## Abstract (arXiv)

We present our first efforts towards building a single multilingual automatic speech recognition (ASR) system that can process code-switching (CS) speech in five languages spoken within the same population. This contrasts with related prior work which focuses on the recognition of CS speech in bilingual scenarios. Recently, we have compiled a small five-language corpus of South African soap opera speech which contains examples of CS between 5 languages occurring in various contexts such as using English as the matrix language and switching to other indigenous languages. The ASR system presented in this work is trained on 4 corpora containing English-isiZulu, English-isiXhosa, English-Setswana and English-Sesotho CS speech. The interpolation of multiple language models trained on these language pairs enables the ASR system to hypothesize mixed word sequences from these 5 languages. We evaluate various state-of-the-art acoustic models trained on this 5-lingual training data and report ASR accuracy and language recognition performance on the development and test sets of the South African multilingual soap opera corpus.