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Evaluating Automatic Speech Recognition Systems for Korean Meteorological Experts

arXiv 2410.18444 ↗First posted 24 Oct 2024cs.CL cs.SD eess.AScited by 0

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Abstract (arXiv)

This paper explores integrating Automatic Speech Recognition (ASR) into natural language query systems to improve weather forecasting efficiency for Korean meteorologists. We address challenges in developing ASR systems for the Korean weather domain, specifically specialized vocabulary and Korean linguistic intricacies. To tackle these issues, we constructed an evaluation dataset of spoken queries recorded by native Korean speakers. Using this dataset, we assessed various configurations of a multilingual ASR model family, identifying performance limitations related to domain-specific terminology. We then implemented a simple text-to-speech-based data augmentation method, which improved the recognition of specialized terms while maintaining general-domain performance. Our contributions include creating a domain-specific dataset, comprehensive ASR model evaluations, and an effective augmentation technique. We believe our work provides a foundation for future advancements in ASR for the Korean weather forecasting domain.

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References · 16

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  2. 2023GPT-4 Technical Reportcited by 18,396
  3. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  4. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 4,057
  5. 2019The Curious Case of Neural Text Degenerationcited by 2,916
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  7. 2021SPGISpeech: 5,000 hours of transcribed financial audio for fully formatted end-to-end speech recognitioncited by 78
  8. 2021Scaling End-to-End Models for Large-Scale Multilingual ASRcited by 61
  9. 2022Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expectcited by 47
  10. 2020Using Synthetic Audio to Improve The Recognition of Out-Of-Vocabulary Words in End-To-End ASR Systemscited by 41
  11. 2024LoRA-Whisper: Parameter-Efficient and Extensible Multilingual ASRcited by 36
  12. 2019Adversarially Trained End-to-end Korean Singing Voice Synthesis Systemcited by 22
4 more
  1. 2022A Survey of Multilingual Models for Automatic Speech Recognitioncited by 21
  2. 2023Multilingual DistilWhisper: Efficient Distillation of Multi-task Speech Models via Language-Specific Expertscited by 17
  3. 2020ClovaCall: Korean Goal-Oriented Dialog Speech Corpus for Automatic Speech Recognition of Contact Centerscited by 13
  4. 2024VietMed: A Dataset and Benchmark for Automatic Speech Recognition of Vietnamese in the Medical Domaincited by 9

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