CS-FLEURS: A Massively Multilingual and Code-Switched Speech Dataset
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Abstract (arXiv)
We present CS-FLEURS, a new dataset for developing and evaluating code-switched speech recognition and translation systems beyond high-resourced languages. CS-FLEURS consists of 4 test sets which cover in total 113 unique code-switched language pairs across 52 languages: 1) a 14 X-English language pair set with real voices reading synthetically generated code-switched sentences, 2) a 16 X-English language pair set with generative text-to-speech 3) a 60 {Arabic, Mandarin, Hindi, Spanish}-X language pair set with the generative text-to-speech, and 4) a 45 X-English lower-resourced language pair test set with concatenative text-to-speech. Besides the four test sets, CS-FLEURS also provides a training set with 128 hours of generative text-to-speech data across 16 X-English language pairs. Our hope is that CS-FLEURS helps to broaden the scope of future code-switched speech research. Dataset link: https://huggingface.co/datasets/byan/cs-fleurs.
Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 27 of its 37 references that are in the map. First posted on arXiv 17 Sep 2025.
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27 of 37 references.
References · 27
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15 more
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Citing papers per year: 2025: 3; 2026: 9.
12 papers.
- 2025Hearing to Translate: The Effectiveness of Speech Modality Integration into LLMscited by 7
- 2025MathMist: A Parallel Multilingual Benchmark Dataset for Mathematical Problem Solving and Reasoningcited by 6
- 2025HiKE: Hierarchical Evaluation Framework for Korean-English Code-Switching Speech Recognitioncited by 4
- 2026ViMedCSS: A Vietnamese Medical Code-Switching Speech Dataset & Benchmarkcited by 3
- 2026Improving Code-Switching ASR with Code-Mixing Guided Synthetic Speechcited by 1
- 2026Towards Truly Multilingual ASR: Generalizing Code-Switching ASR to Unseen Language Pairscited by 0
- 2026Contrastive Training with LLM-generated Near-Misses for Robust Code-Switching Speech Recognitioncited by 0
- 2026Adding Robust Code-Switching Capabilities to High Performance Multilingual ASRcited by 0
- 2026Reinforcement Learning for Data-Efficient Code-Switched ASRcited by 0
- 2026Code-Switching Spoken Language Identification as Multi-Label Set Predictioncited by 0
- 2026Phonological Interference in Multilingual Speech Modelscited by 0
- 2026Code-Switching Detection via Language-Selective Dimensions in Speech Foundation Modelscited by 0
- 2026Code-Switching Detection via Language-Selective Dimensions in Speech Foundation Models13 Oct 2026
- 2026Phonological Interference in Multilingual Speech Models8 Oct 2026
- 2026Code-Switching Spoken Language Identification as Multi-Label Set Prediction1 Oct 2026
- 2026Reinforcement Learning for Data-Efficient Code-Switched ASR2 Jul 2026
- 2026Adding Robust Code-Switching Capabilities to High Performance Multilingual ASR20 Jun 2026
- 2026Improving Code-Switching ASR with Code-Mixing Guided Synthetic Speech14 Jun 2026
- 2026Contrastive Training with LLM-generated Near-Misses for Robust Code-Switching Speech Recognition5 Jun 2026
- 2026Towards Truly Multilingual ASR: Generalizing Code-Switching ASR to Unseen Language Pairs4 Jun 2026
- 2026ViMedCSS: A Vietnamese Medical Code-Switching Speech Dataset & Benchmark13 Feb 2026
- 2025Hearing to Translate: The Effectiveness of Speech Modality Integration into LLMs18 Dec 2025
- 2025MathMist: A Parallel Multilingual Benchmark Dataset for Mathematical Problem Solving and Reasoning16 Oct 2025
- 2025HiKE: Hierarchical Evaluation Framework for Korean-English Code-Switching Speech Recognition29 Sep 2025