Representation of glottal shape data for signal processing

Westphal, Louis C.; Childers, D. G.

doi:10.1109/tassp.1983.1164104

Cited by 9 publications

(9 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1, 2010 Clinically, real-time processing of thousands of high-speed image frames requires that an image detection method be automatic, and in particular, should be highly efficient in extracting vocal fold vibratory patterns. 7,9 The implementation of the parameter extraction methods in our previous study 18 depend on efficient extraction of the vocal fold edges. To investigate the computation efficiency, we calculate the computation times of the histogram method, active contour method, and our method to process 100 high-speed image frames from each larynx, as shown in Figure 6.…”

Section: Resultsmentioning

confidence: 99%

“…14 Image resolutions lower than those in our excised larynx experiments have been applied in clinical practice. [6][7][8][9][10][11][12][13][14] In addition, due to the presence of arytenoid cartilages and other surrounding tissues, it is often necessary to reduce the size of the field of view to capture the vocal folds, which results in a decreased image resolution for edge detection. Because of these two facts, it is necessary to examine the results of our method under reduced image resolution conditions.…”

Section: Resultsmentioning

confidence: 99%

“…In recent years, with the development of high-speed digital imaging, various automatic image detection algorithms have been applied. 6,7,9,[12][13][14] In this study, we consider two of the most popular methods, the histogram and active contour algorithms, to automatically detect vocal fold edges.…”

Section: Image Detection Algorithmmentioning

confidence: 99%

“…High-speed digital imaging is emerging as a valuable clinical tool for the direct measurement of vocal fold vibrations. [6][7][8][9][10][11][12][13][14][15] High-speed imaging systems record images of the larynx at a rate as high as 4000 frames/second, and are capable of resolving actual vibrations of the vocal folds. Yan et al 2,6 applied automatic tracing of vocal fold movement to extract glottal area of normal subjects and patients.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Efficient and Effective Extraction of Vocal Fold Vibratory Patterns from High-Speed Digital Imaging

et al. 2010

View full text Add to dashboard Cite

High-speed digital imaging can provide valuable information on disordered voice production in voice science. However, the large amounts of high-speed image data with limited image resolutions produce significant challenges for computer analysis, and thus effective and efficient image edge extraction methods allowing for the batch analysis of high-speed images of vocal folds is clinically important. In this paper, a novel algorithm for automatic image edge detection is proposed to effectively and efficiently process high-speed images of the vocal folds. The method integrates Lagrange interpolation, differentiation, and Canny edge detection, which allow objective extraction of aperiodic vocal fold vibratory patterns from large numbers of high-speed digital images. This method and two other popular algorithms, histogram and active contour, are performed on 10 sets of high-speed video data from excised larynx experiments to compare their performances in analyzing high-speed images. The accuracy in computing glottal area and the computation time of these methods are investigated. The results show that our proposed method provides the most accurate and efficient detection, and is applicable when processing low-resolution images. In this study, we focus on developing a method to effectively and efficiently process high-speed image data from excised larynges. However, in addition we show the clinical potential of this method by use of example high-speed image data obtained from a patient with vocal nodules.The proposed automatic image-processing algorithm may provide a valuable biomedical application for the clinical assessment of vocal disorders by use of high-speed digital imaging.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Image Detection Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Efficient and Effective Extraction of Vocal Fold Vibratory Patterns from High-Speed Digital Imaging

et al. 2010

View full text Add to dashboard Cite

show abstract

“…However, up to the present there is still no established feature extraction strategy describing the entire vibration patterns of vocal fold dynamics adequately. Recently, the novel Phonovibrogram (PVG) approach was suggested to quantify the entire visible vocal fold vibrations (Lohscheller et al, 2007;Lohscheller et al, 2008a) expanding formerly introduced spatio-temporal plots (Westphal & Childers, 1983;Neubauer et al, 2001). In the PVG approach, contours of the oscillating vocal folds are segmented from video data and are transformed into a single colour coded PVG image.…”

Section: Introductionmentioning

confidence: 99%

Support Vector Machine Classification of Vocal Fold Vibrations Based on Phonovibrogram Features

Döllinger¹,

Lohscheller²,

Švec³

et al. 2011

Advances in Vibration Analysis Research

View full text Add to dashboard Cite

Measurement of Glottal Cycle Characteristics Between Children and Adults: Physiological Variations

Patel¹,

Dubrovskiy²,

Döllinger³

2014

Journal of Voice

View full text Add to dashboard Cite

Objective The aim of this study is to quantify phases of the vibratory cycle using measurements of glottal cycle quotients and glottal cycle derivatives, in typically developing pre-pubertal children and young adults with use of high speed digital imaging (HSDI). Method Vocal fold vibrations were recorded from 27 children (age range 5–9 years) and 35 adults (age range 21–45 years), with HSDI at 4000 frames per second for sustained phonation. Glottal area waveform (GAW) measures of Open Quotient (OQ), Closing Quotient (CQ), Speed Index (SI), Rate Quotient (RQ) and Asymmetry Quotient (AsyQ) were computed. Glottal cycle derivatives of Amplitude Quotient (AQ) and Maximum Area Declination Rate (MADR) were also computed. Group differences (adult females, adult males, and children) were statistically investigated for mean and standard deviation values of the glottal cycle quotients and glottal cycle derivatives. Results Children exhibited higher values of Speed Index, Asymmetry Quotient and lower MADR compared to adult males. Children exhibited the highest mean value and lowest variability in Amplitude Quotient compared to adult males and females. Adult males showed lower values of Speed Index, Asymmetry Quotient, Amplitude Quotient and higher values of MADR compared to adult females. Conclusion Glottal cycle vibratory motion in children is functionally different compared to adult males and females; suggesting the need for development of children specific norms for both normal and disordered voice qualities.

show abstract

Representation of glottal shape data for signal processing

Cited by 9 publications

References 2 publications

Efficient and Effective Extraction of Vocal Fold Vibratory Patterns from High-Speed Digital Imaging

Efficient and Effective Extraction of Vocal Fold Vibratory Patterns from High-Speed Digital Imaging

Support Vector Machine Classification of Vocal Fold Vibrations Based on Phonovibrogram Features

Measurement of Glottal Cycle Characteristics Between Children and Adults: Physiological Variations

Contact Info

Product

Resources

About