Limitations of Source-Filter Coupling In Phonation
The coupling of vocal fold (source) and vocal tract (filter) is one of the most critical factors in source-filter articulation theory. The traditional linear source-filter theory has been challenged by current research which clearly shows the impact of acoustic loading on the dynamic behavior of the vocal fold vibration as well as the variations in the glottal flow pulses shape. This paper outlines the underlying mechanism of source-filter interactions; demonstrates the design and working principles of coupling for the various existing vocal cord and vocal tract biomechanical models. For our study, we have considered self-oscillating lumped-element models of the acoustic source and computational models of the vocal tract as articulators. To understand the limitations of source-filter interactions which are associated with each of those models, we compare them concerning their mechanical design, acoustic and physiological characteristics and aerodynamic simulation.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
A Manually Annotated Resource for the Investigation of Nasal Grunts
This paper presents an annotation framework for nasal grunts of the whole French CID corpus (Bertrand et al., 2008). The acoustic components under scrutiny are justified and the annotation guidelines are described. We ca…
Towards detecting the pathological subharmonic voicing with fully convolutional neural networks
Many voice disorders induce subharmonic phonation, but voice signal analysis is currently lacking a technique to detect the presence of subharmonics reliably. Distinguishing subharmonic phonation from normal phonation is…
Residual Attention Based Network for Automatic Classification of Phonation Modes
Phonation mode is an essential characteristic of singing style as well as an important expression of performance. It can be classified into four categories, called neutral, breathy, pressed and flow. Previous studies use…
ClassificationFeature EngineeringInformation RetrievalMusic Information Retrieval+1Learning and controlling the source-filter representation of speech with a variational autoencoder
Understanding and controlling latent representations in deep generative models is a challenging yet important problem for analyzing, transforming and generating various types of data. In speech processing, inspiring from…
voice2mode: Phonation Mode Classification in Singing using Self-Supervised Speech Models
We present voice2mode, a method for classification of four singing phonation modes (breathy, neutral (modal), flow, and pressed) using embeddings extracted from large self-supervised speech models. Prior work on singing …
Speech Recognition