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Related Concept Videos

  1. Home
  3. Research Domains
  5. Language, Communication And Culture
  7. Language Studies
  9. German Language
  11. Girafe: Glottal Imaging Dataset For Advanced Segmentation, Analysis, And Facilitative Playbacks Evaluation.
  1. Home
  3. Research Domains
  5. Language, Communication And Culture
  7. Language Studies
  9. German Language
  11. Girafe: Glottal Imaging Dataset For Advanced Segmentation, Analysis, And Facilitative Playbacks Evaluation.

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GIRAFE: Glottal imaging dataset for advanced segmentation, analysis, and facilitative playbacks evaluation.

Gustavo Andrade-Miranda1,2, Konstantinos Chatzipapas1,3, Julián D Arias-Londoño4

  • 1Laboratoire de Traitement de l'Information Médicale (LaTIM), UMR 1101, INSERM, University of Brest, 29200, Brest, France.

Data in Brief
|March 3, 2025

View abstract on PubMed

Summary
This summary is machine-generated.

A new dataset, GIRAFE, addresses the lack of annotated vocal fold images for developing advanced glottal gap segmentation techniques. This resource aids research in high-speed videoendoscopic analysis and facilitative playback evaluation.

Keywords:
Facilitative playbacksGlottal gap segmentationHigh-speed imagingLaryngeal videoendoscopy

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Area of Science:

  • Medical Imaging
  • Bioengineering
  • Vocal Fold Dynamics

Background:

  • Facilitative playback development from high-speed videoendoscopic sequences is limited by scarce, annotated vocal fold datasets.
  • Lack of semantic segmentation data for the glottal gap hinders reproducibility and research exploration in this field.

Purpose of the Study:

  • To introduce GIRAFE, a novel data repository for vocal fold analysis.
  • To facilitate the development of advanced semantic segmentation and analysis techniques for high-speed videoendoscopic sequences.

Main Methods:

  • Compilation of 65 high-speed videoendoscopic recordings from 50 patients (healthy, voice disorder, unknown condition).
  • Manual annotation of glottal gap semantic segmentation masks by an expert.
  • Inclusion of automatic glottal area segmentation using state-of-the-art methods.

Main Results:

  • The GIRAFE dataset supports studies on glottal gap segmentation algorithms.
  • It aids in improving and creating new facilitative playback techniques from high-speed videoendoscopic data.

Conclusions:

  • GIRAFE addresses the critical need for annotated vocal fold imaging data.
  • The challenge of fully automatic, accurate glottal area semantic segmentation remains an open research area.