Abstract
The objective assessment of the vocal fold vibrations is important in diagnosing several vocal diseases. Given the high speed of the vibrations, the high speed videoendoscopy is commonly used to capture the vocal fold movements into video recordings. Commonly, two steps are carried out in order to automatically quantify laryngeal parameters and assess the vibrations. The first step aims to map the spatial-temporal information contained in the video recordings into a representation that facilitates the analysis of the vibrations. Numerous techniques are reported in the literature but the majority of them require the segmentation of all the images of the video, which is a complex task. The second step aims to quantify laryngeal parameters in order to assess the vibrations. To this aim, most of the existing approaches require an additional processing to the representation in order to deduce those parameters. Furthermore, for some reported representations, the assessment of the symmetry and the periodicity of the vocal fold dynamics needs setting up parameters that are specific to the representation under consideration; which makes difficult the comparison between the existing techniques. To alleviate these problems, the present study investigates the use of a recently proposed representation named optical flow based waveform, in order to objectively quantify the laryngeal parameters. This waveform is retained in this study as it does not require the segmentation of all the images of the video. Furthermore, it will be shown in the present work that the automatic quantification of the vibrations using this waveform can be carried out without applying any additional processing. Moreover, common laryngeal parameters are exploited; hence, no specific parameters are needed to be defined for the automatic assessment of the vibrations. Experiments conducted on healthy and pathological phonation show the accuracy of the waveform. Besides, it is more sensitive to pathological phonation than the state-of-the-art techniques.