VietMed: Vietnamese Medical Speech Recognition Dataset

VietMed is a Vietnamese speech recognition dataset for the medical domain. It comprises 16 hours of labeled medical speech, 1000 hours of unlabeled medical speech, and 1200 hours of unlabeled general-domain speech. The dataset was introduced by leduckhai for the LREC-COLING 2024 conference.

Use Cases

• Train automatic speech recognition models based on labeled medical speech.
• Perform self-supervised or semi-supervised learning based on the large volume of unlabeled medical speech.
• Fine-tune general-domain speech models for the medical domain using the labeled subset.
• Benchmark speech recognition performance in the Vietnamese medical context.

Strengths

• Contains 16 hours of labeled medical speech data.
• Includes a large auxiliary corpus of 1000 hours of unlabeled medical speech.
• Provides an additional 1200 hours of unlabeled general-domain speech for broader context.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

huggingface

Freshness

Last updated 2025-06-02 19:21:14; freshness should be verified.