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United-Syn-Med

Introduced by Sourav Banerjee et al. in High-precision medical speech recognition through synthetic data and semantic correction: UNITED-MEDASR23 Oct 2024 archive 2025-07-28

The United-Syn-Med dataset is a specialized medical speech dataset designed to evaluate and improve Automatic Speech Recognition (ASR) systems within the healthcare domain. It comprises English medical speech recordings, with a particular focus on medical terminology and clinical conversations. The dataset is well-suited for various ASR tasks, including speech recognition, transcription, and classification, facilitating the development of models tailored for medical contexts.

This dataset supports a broad range of applications, including medical documentation automation, transcription of doctor-patient conversations, and medical knowledge extraction from audio data.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

Creative Commons Attribution Share Alike 4.0

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • United-Syn-Med

1 variant name, as the archive lists them.

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