Automated Detection of Voice Disorder in the Saarbrücken Voice Database: Effects of Pathology Subset and Audio Materials

2021 ◽  
Author(s):  
Mark Huckvale ◽  
Catinca Buciuleac
Keyword(s):  
Automated Detection ◽  
Voice Disorder

Assessment of Tongue Position and Laryngeal Height in Two Professional Voice Populations

2020 ◽  
Vol 63 (1) ◽  
pp. 109-124
Author(s):  
Carly Jo Hosbach-Cannon ◽  
Soren Y. Lowell ◽  
Raymond H. Colton ◽  
Richard T. Kelley ◽  
Xue Bao
Keyword(s):  
Vocal Fold ◽  
Vocal Tract ◽  
Current Knowledge ◽  
Acoustic Resonance ◽  
Contact Dynamics ◽  
Voice Disorder ◽  
Music Program ◽  
Tongue Position ◽  
Singer Groups ◽  
Professional Voice

Purpose To advance our current knowledge of singer physiology by using ultrasonography in combination with acoustic measures to compare physiological differences between musical theater (MT) and opera (OP) singers under controlled phonation conditions. Primary objectives addressed in this study were (a) to determine if differences in hyolaryngeal and vocal fold contact dynamics occur between two professional voice populations (MT and OP) during singing tasks and (b) to determine if differences occur between MT and OP singers in oral configuration and associated acoustic resonance during singing tasks. Method Twenty-one singers (10 MT and 11 OP) were included. All participants were currently enrolled in a music program. Experimental procedures consisted of sustained phonation on the vowels /i/ and /ɑ/ during both a low-pitch task and a high-pitch task. Measures of hyolaryngeal elevation, tongue height, and tongue advancement were assessed using ultrasonography. Vocal fold contact dynamics were measured using electroglottography. Simultaneous acoustic recordings were obtained during all ultrasonography procedures for analysis of the first two formant frequencies. Results Significant oral configuration differences, reflected by measures of tongue height and tongue advancement, were seen between groups. Measures of acoustic resonance also showed significant differences between groups during specific tasks. Both singer groups significantly raised their hyoid position when singing high-pitched vowels, but hyoid elevation was not statistically different between groups. Likewise, vocal fold contact dynamics did not significantly differentiate the two singer groups. Conclusions These findings suggest that, under controlled phonation conditions, MT singers alter their oral configuration and achieve differing resultant formants as compared with OP singers. Because singers are at a high risk of developing a voice disorder, understanding how these two groups of singers adjust their vocal tract configuration during their specific singing genre may help to identify risky vocal behavior and provide a basis for prevention of voice disorders.

Multiple Perspectives on the Barriers to Identification and Management of Pediatric Voice Disorders

2017 ◽  
Vol 2 (3) ◽  
pp. 49-56
Author(s):  
Jana Childes ◽  
Alissa Acker ◽  
Dana Collins
Keyword(s):  
Academic Success ◽  
Voice Disorders ◽  
School Personnel ◽  
Voice Disorder ◽  
Multiple Perspectives ◽  
Vocal Qualities ◽  
High Prevalence ◽  
Pediatric Populations ◽  
Low Incidence ◽  
University Settings

Pediatric voice disorders are typically a low-incidence population in the average caseload of clinicians working within school and general clinic settings. This occurs despite evidence of a fairly high prevalence of childhood voice disorders and the multiple impacts the voice disorder may have on a child's social development, the perception of the child by others, and the child's academic success. There are multiple barriers that affect the identification of children with abnormal vocal qualities and their access to services. These include: the reliance on school personnel, the ability of parents and caretakers to identify abnormal vocal qualities and signs of misuse, the access to specialized medical services for appropriate diagnosis, and treatment planning and issues related to the Speech-Language Pathologists' perception of their skills and competence regarding voice management for pediatric populations. These barriers and possible solutions to them are discussed with perspectives from the school, clinic and university settings.

Automated detection of epithelial changes in colorectal carcinoma

2012 ◽  
Vol 50 (05) ◽  
Author(s):  
G Valcz ◽  
I Bándi ◽  
B Wichmann ◽  
A Patai ◽  
D Szabó ◽  
...  
Keyword(s):  
Colorectal Carcinoma ◽  
Automated Detection

Machine Learning in Agriculture

2018 ◽  
Vol 8 (6) ◽  
pp. 26 ◽  
Author(s):  
Matthew N. O. Sadiku ◽  
Chandra M. M Kotteti ◽  
Sarhan M. Musa
Keyword(s):  
Climate Change ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Disease Diagnosis ◽  
Automated Detection ◽  
Disease Prediction ◽  
Paper Briefly ◽  
Agriculture Sector ◽  
Modern Agriculture ◽  
Crop Disease

Machine learning is an emerging field of artificial intelligence which can be applied to the agriculture sector. It refers to the automated detection of meaningful patterns in a given data.  Modern agriculture seeks ways to conserve water, use nutrients and energy more efficiently, and adapt to climate change.  Machine learning in agriculture allows for more accurate disease diagnosis and crop disease prediction. This paper briefly introduces what machine learning can do in the agriculture sector.

Automated Detection of Pin Defects on Counterfeit Microelectronics

2018 ◽  
Author(s):  
Pallabi Ghosh ◽  
Domenic Forte ◽  
Damon L. Woodard ◽  
Rajat Subhra Chakraborty
Keyword(s):  
Integrated Circuits ◽  
Depth Map ◽  
Optical Microscope ◽  
Automated Detection ◽  
Detection Methods ◽  
Global Supply Chains ◽  
Subject Matter Experts ◽  
Security Breaches ◽  
The Past ◽  
Skilled Subject

Abstract Counterfeit electronics constitute a fast-growing threat to global supply chains as well as national security. With rapid globalization, the supply chain is growing more and more complex with components coming from a diverse set of suppliers. Counterfeiters are taking advantage of this complexity and replacing original parts with fake ones. Moreover, counterfeit integrated circuits (ICs) may contain circuit modifications that cause security breaches. Out of all types of counterfeit ICs, recycled and remarked ICs are the most common. Over the past few years, a plethora of counterfeit IC detection methods have been created; however, most of these methods are manual and require highly-skilled subject matter experts (SME). In this paper, an automated bent and corroded pin detection methodology using image processing is proposed to identify recycled ICs. Here, depth map of images acquired using an optical microscope are used to detect bent pins, and segmented side view pin images are used to detect corroded pins.

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