Glottal Source Processing: from Analysis to Applications
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Abstract (arXiv)
The great majority of current voice technology applications relies on acoustic features characterizing the vocal tract response, such as the widely used MFCC of LPC parameters. Nonetheless, the airflow passing through the vocal folds, and called glottal flow, is expected to exhibit a relevant complementarity. Unfortunately, glottal analysis from speech recordings requires specific and more complex processing operations, which explains why it has been generally avoided. This review gives a general overview of techniques which have been designed for glottal source processing. Starting from fundamental analysis tools of pitch tracking, glottal closure instant detection, glottal flow estimation and modelling, this paper then highlights how these solutions can be properly integrated within various voice technology applications.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Dec 2019.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 1.
3 papers.
- 2021Neural Analysis and Synthesis: Reconstructing Speech from Self-Supervised Representationscited by 81
- 2023Investigation of Self-supervised Pre-trained Models for Classification of Voice Quality from Speech and Neck Surface Accelerometer Signalscited by 2
- 2024Modeling and Estimation of Vocal Tract and Glottal Source Parameters Using ARMAX-LF Modelcited by 0
- 2024Modeling and Estimation of Vocal Tract and Glottal Source Parameters Using ARMAX-LF Model7 Oct 2024
- 2023Investigation of Self-supervised Pre-trained Models for Classification of Voice Quality from Speech and Neck Surface Accelerometer Signals6 Aug 2023
- 2021Neural Analysis and Synthesis: Reconstructing Speech from Self-Supervised Representations27 Oct 2021