Model Card for Fine-Tuned Whisper Model: Hypernasality Identification

This model card details the Whisper model, fine-tuned to identify hypernasality in patients from audio recordings. The model is developed to assist in the diagnosis and monitoring of speech disorders.

Model Details

Model Description

  • Developed by: The Data Science team at the Vanderbilt Data Science Institute
  • Funded by: This project was supported by healthcare-focused research grants and institutional funding.
  • Shared by: The model is shared by Vanderbilt University with the aim to assist clinicians and speech therapists.
  • Model type: Deep Learning, Neural Network (Fine-Tuned Whisper Model)
  • Language(s) (NLP): The model primarily focuses on English language audio samples but has the potential to be adapted for multilingual use.
  • License: The model is released under an open-source license for non-commercial use, details of which can be found in the repository.
  • Finetuned from model: The base model is OpenAI's Whisper, which has been fine-tuned using a specialized dataset for hypernasality detection.

Model Sources

Uses

Direct Use

  • This model can be directly used by healthcare professionals to analyze patient speech samples for signs of hypernasality, aiding in diagnosis and treatment planning.

Downstream Use

  • Potential use in automated speech therapy tools or in research settings for studying speech disorders.

Out-of-Scope Use

  • Not intended for non-medical use or as a sole diagnostic tool without clinical oversight.

Bias, Risks, and Limitations

  • The model might have limitations in accurately identifying hypernasality across diverse accents and languages. User discretion is advised, and results should be considered alongside clinical assessments.

Recommendations

  • Healthcare professionals should use this tool as a supplement to traditional diagnostic methods. Continuous updating with diverse datasets is recommended to improve accuracy.

How to Get Started with the Model

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