ArticleScientific data2020
Printable 3D vocal tract shapes from MRI data and their acoustic and aerodynamic properties.
Article in Scientific data, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Multi-Atlas-Based Segmentation of Pediatric Vocal Tract Anatomy in Dynamic Magnetic Resonance Imaging.Journal of speech, language, and hearing research : JSLHR · 2026Article
- Thermoacoustic Curing Mechanism and Process Optimization in Non-Contact Ultrasonic 3D Printing.Materials (Basel, Switzerland) · 2026Article
- Open-Source Manually Annotated Vocal Tract Database for Automatic Segmentation from 3D MRI Using Deep Learning: Benchmarking 2D and 3D Convolutional and Transformer Networks.Journal of voice : official journal of the Voice Foundation · 2025Article
- Investigation Methods for Vocal Onset-A Historical Perspective.Bioengineering (Basel, Switzerland) · 2024Article
- Assessing accuracy of resonances obtained with reassigned spectrograms from the "ground truth" of physical vocal tract models.The Journal of the Acoustical Society of America · 2024Article
- Voice efficiency for different voice qualities combining experimentally derived sound signals and numerical modeling of the vocal tract.Frontiers in physiology · 2022Article
- Multimodal dataset of real-time 2D and static 3D MRI of healthy French speakers.Scientific data · 2021Article
- Printable 3D vocal tract shapes from MRI data and their acoustic and aerodynamic properties.Scientific data · 2020Article
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Authors and funding
6 authors.
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Abstract
A detailed understanding of how the acoustic patterns of speech sounds are generated by the complex 3D shapes of the vocal tract is a major goal in speech research. The Dresden Vocal Tract Dataset (DVTD) presented here contains geometric and (aero)acoustic data of the vocal tract of 22 German speech sounds (16 vowels, 5 fricatives, 1 lateral), each from one male and one female speaker. The data include the 3D Magnetic Resonance Imaging data of the vocal tracts, the corresponding 3D-printable and finite-element models, and their simulated and measured acoustic and aerodynamic properties. The dataset was evaluated in terms of the plausibility and the similarity of the resonance frequencies determined by the acoustic simulations and measurements, and in terms of the human identification rate of the vowels and fricatives synthesized by the artificially excited 3D-printed vocal tract models. According to both the acoustic and perceptual metrics, most models are accurate representations of the intended speech sounds and can be readily used for research and education.
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