VietMed：越南语医疗领域语音识别数据集与基准

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Abstract:Due to privacy restrictions, there's a shortage of publicly available speech recognition datasets in the medical domain. In this work, we present VietMed - a Vietnamese speech recognition dataset in the medical domain comprising 16h of labeled medical speech, 1000h of unlabeled medical speech and 1200h of unlabeled general-domain speech. To our best knowledge, VietMed is by far the world's largest public medical speech recognition dataset in 7 aspects: total duration, number of speakers, diseases, recording conditions, speaker roles, unique medical terms and accents. VietMed is also by far the largest public Vietnamese speech dataset in terms of total duration. Additionally, we are the first to present a medical ASR dataset covering all ICD-10 disease groups and all accents within a country. Moreover, we release the first public large-scale pre-trained models for Vietnamese ASR, w2v2-Viet and XLSR-53-Viet, along with the first public large-scale fine-tuned models for medical ASR. Even without any medical data in unsupervised pre-training, our best pre-trained model XLSR-53-Viet generalizes very well to the medical domain by outperforming state-of-the-art XLSR-53, from 51.8% to 29.6% WER on test set (a relative reduction of more than 40%). All code, data and models are made publicly available: this https URL.

Comments:	LREC-COLING 2024 (Oral)
Subjects:	Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Audio and Speech Processing (eess.AS)
Cite as:	arXiv:2404.05659 [cs.CL]
	(or arXiv:2404.05659v4 [cs.CL] for this version)
	https://doi.org/10.48550/arXiv.2404.05659 arXiv-issued DOI via DataCite

Submission history

From: Khai Le-Duc [view email]
[v1] Mon, 8 Apr 2024 16:43:52 UTC (353 KB)
[v2] Tue, 28 May 2024 05:27:48 UTC (351 KB)
[v3] Fri, 4 Apr 2025 15:06:21 UTC (1,194 KB)
[v4] Fri, 16 Oct 2026 07:21:38 UTC (323 KB)