# Towards End-to-End Code-Switching Speech Recognition

arXiv: https://arxiv.org/abs/1810.13091 · HTML: https://mlsanity.com/paper/1810.13091/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Oct 2018.

## Built on by (most cited first, 17 of 17)

- [End-to-End Speech Translation for Code Switched Speech](https://mlsanity.com/paper/2204.05076/) (2022)
- [Language-Routing Mixture of Experts for Multilingual and Code-Switching Speech Recognition](https://mlsanity.com/paper/2307.05956/) (2023)
- [Streaming End-to-End Multilingual Speech Recognition with Joint Language Identification](https://mlsanity.com/paper/2209.06058/) (2022)
- [Joint Modeling of Code-Switched and Monolingual ASR via Conditional Factorization](https://mlsanity.com/paper/2111.15016/) (2021)
- [TALCS: An Open-Source Mandarin-English Code-Switching Corpus and a Speech Recognition Baseline](https://mlsanity.com/paper/2206.13135/) (2022)
- [Investigations on Speech Recognition Systems for Low-Resource Dialectal Arabic-English Code-Switching Speech](https://mlsanity.com/paper/2108.12881/) (2021)
- [Code-Switching Text Generation and Injection in Mandarin-English ASR](https://mlsanity.com/paper/2303.10949/) (2023)
- [Multilingual self-supervised speech representations improve the speech recognition of low-resource African languages with codeswitching](https://mlsanity.com/paper/2311.15077/) (2023)
- [An Effective Mixture-Of-Experts Approach For Code-Switching Speech Recognition Leveraging Encoder Disentanglement](https://mlsanity.com/paper/2402.17189/) (2024)
- [Language-agnostic Code-Switching in Sequence-To-Sequence Speech Recognition](https://mlsanity.com/paper/2210.08992/) (2022)
- [Generative error correction for code-switching speech recognition using large language models](https://mlsanity.com/paper/2310.13013/) (2023)
- [Synthetic Data Generation and Joint Learning for Robust Code-Mixed Translation](https://mlsanity.com/paper/2403.16771/) (2024)
- [Code-Switching in End-to-End Automatic Speech Recognition: A Systematic Literature Review](https://mlsanity.com/paper/2507.07741/) (2025)
- [Balanced End-to-End Monolingual pre-training for Low-Resourced Indic Languages Code-Switching Speech Recognition](https://mlsanity.com/paper/2106.05885/) (2021)
- [Summary on the ISCSLP 2022 Chinese-English Code-Switching ASR Challenge](https://mlsanity.com/paper/2210.06091/) (2022)
- [The evaluation of a code-switched Sepedi-English automatic speech recognition system](https://mlsanity.com/paper/2403.07947/) (2024)
- [The Exact Worst-Case Tail Probability under Bounded Kurtosis](https://mlsanity.com/paper/2607.05226/) (2026)

## Abstract (arXiv)

Code-switching speech recognition has attracted an increasing interest recently, but the need for expert linguistic knowledge has always been a big issue. End-to-end automatic speech recognition (ASR) simplifies the building of ASR systems considerably by predicting graphemes or characters directly from acoustic input. In the mean time, the need of expert linguistic knowledge is also eliminated, which makes it an attractive choice for code-switching ASR. This paper presents a hybrid CTC-Attention based end-to-end Mandarin-English code-switching (CS) speech recognition system and studies the effect of hybrid CTC-Attention based models, different modeling units, the inclusion of language identification and different decoding strategies on the task of code-switching ASR. On the SEAME corpus, our system achieves a mixed error rate (MER) of 34.24%.