mlsanityData to 14 Oct 2026

Speech collage: code-switched audio generation by collaging monolingual corpora

arXiv 2309.15674 ↗First posted 27 Sep 2023cs.SD cs.CL cs.LGcited by 10

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Abstract (arXiv)

Designing effective automatic speech recognition (ASR) systems for Code-Switching (CS) often depends on the availability of the transcribed CS resources. To address data scarcity, this paper introduces Speech Collage, a method that synthesizes CS data from monolingual corpora by splicing audio segments. We further improve the smoothness quality of audio generation using an overlap-add approach. We investigate the impact of generated data on speech recognition in two scenarios: using in-domain CS text and a zero-shot approach with synthesized CS text. Empirical results highlight up to 34.4% and 16.2% relative reductions in Mixed-Error Rate and Word-Error Rate for in-domain and zero-shot scenarios, respectively. Lastly, we demonstrate that CS augmentation bolsters the model's code-switching inclination and reduces its monolingual bias.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 23 of its 40 references that are in the map. First posted on arXiv 27 Sep 2023.

Builds on

23 of 40 references.

References · 23

  1. 2018SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processingcited by 1,989
  2. 2020Conformer: Convolution-augmented Transformer for Speech Recognitioncited by 1,863
  3. 2017AISHELL-1: An Open-Source Mandarin Speech Corpus and A Speech Recognition Baselinecited by 373
  4. 2018TED-LIUM 3: twice as much data and corpus repartition for experiments on speaker adaptationcited by 226
  5. 2021Word Alignment by Fine-tuning Embeddings on Parallel Corporacited by 186
  6. 2020Recent Developments on ESPnet Toolkit Boosted by Conformercited by 132
  7. 2019A Survey of Code-switched Speech and Language Processingcited by 75
  8. 2019Speech Recognition with Augmented Synthesized Speechcited by 60
  9. 2021Towards One Model to Rule All: Multilingual Strategy for Dialectal Code-Switching Arabic ASRcited by 41
  10. 2021Lhotse: a speech data representation library for the modern deep learning ecosystemcited by 33
  11. 2020Multi-Encoder-Decoder Transformer for Code-Switching Speech Recognitioncited by 28
  12. 2021On Addressing Practical Challenges for RNN-Transducercited by 19
11 more
  1. 2021Joint Modeling of Code-Switched and Monolingual ASR via Conditional Factorizationcited by 18
  2. 2019Improving Performance of End-to-End ASR on Numeric Sequencescited by 17
  3. 2021Arabic Code-Switching Speech Recognition using Monolingual Datacited by 17
  4. 2020Improving Low Resource Code-switched ASR using Augmented Code-switched TTScited by 15
  5. 2022Towards Zero-Shot Code-Switched Speech Recognitioncited by 15
  6. 2023Code-Switching Text Generation and Injection in Mandarin-English ASRcited by 11
  7. 2020Learning to Recognize Code-switched Speech Without Forgetting Monolingual Speech Recognitioncited by 10
  8. 2022Textual Data Augmentation for Arabic-English Code-Switching Speech Recognitioncited by 10
  9. 2021On-the-Fly Aligned Data Augmentation for Sequence-to-Sequence ASRcited by 9
  10. 2019Training a code-switching language model with monolingual datacited by 6
  11. 2021Balanced End-to-End Monolingual pre-training for Low-Resourced Indic Languages Code-Switching Speech Recognitioncited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 6; 2026: 3.

10 papers.

  1. 2025A Survey of Code-switched Arabic NLP: Progress, Challenges, and Future Directionscited by 5
  2. 2025Can we train ASR systems on Code-switch without real code-switch data? Case study for Singapore's languagescited by 5
  3. 2025Beyond Monolingual Assumptions: A Survey of Code-Switched NLP in the Era of Large Language Models across Modalitiescited by 5
  4. 2025Code-Switching in End-to-End Automatic Speech Recognition: A Systematic Literature Reviewcited by 4
  5. 2025HiKE: Hierarchical Evaluation Framework for Korean-English Code-Switching Speech Recognitioncited by 4
  6. 2024CAMEL: Cross-Attention Enhanced Mixture-of-Experts and Language Bias for Code-Switching Speech Recognitioncited by 3
  7. 2025SAGE: Spliced-Audio Generated Data for Enhancing Foundational Models in Low-Resource Arabic-English Code-Switched Speech Recognitioncited by 2
  8. 2026Improving Code-Switching Speech Recognition with TTS Data Augmentationcited by 2
  9. 2026Direct Preference Optimization for English-Mandarin Code-Switching Speech Recognition in Audio LLMscited by 2
  10. 2026Code-Switching Detection via Language-Selective Dimensions in Speech Foundation Modelscited by 0