Summary of Girafe: Glottal Imaging Dataset For Advanced Segmentation, Analysis, and Facilitative Playbacks Evaluation, by G. Andrade-miranda et al.
GIRAFE: Glottal Imaging Dataset for Advanced Segmentation, Analysis, and Facilitative Playbacks Evaluation
by G. Andrade-Miranda, K. Chatzipapas, J.D. Arias-Londoño, J. I. Godino-Llorente
First submitted to arxiv on: 19 Dec 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Sound (cs.SD); Audio and Speech Processing (eess.AS)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel paper tackles the challenge of annotating High-Speed videoendoscopic sequences of vocal folds, a crucial step for developing Facilitative Playbacks. The proposed approach aims to bridge the gap in publicly available datasets by providing semantic segmentations corresponding to the glottal gap area. This breakthrough has far-reaching implications for the reproducibility and advancement of research in this field. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new study makes it possible to label videos of vocal folds, which is important for creating tools that help with singing and speaking. Right now, there isn’t a big dataset available that’s labeled correctly, making it hard to repeat or build upon existing research. This paper wants to change that by creating a dataset that helps scientists better understand the way our voices work. |
