Background and Objectives: The Eating Assessment Tool (EAT-10) is a 10-item self-administered questionnaire. It is a noninvasive tool to measure patients' perception of their swallowing problems. The purposes of the present study were to develop an Arabic version of the EAT-10 and to evaluate its validity, consistency, and reliability in the Arabic-speaking population with oropharyngeal dysphagia. Setting and Design: This was a prospective study carried out at the Communication and Swallowing Disorders Unit, King Saud University, Riyadh, Saudi Arabia. Subjects and Methods: The Arabic EAT-10 was administered to 138 patients with oropharyngeal dysphagia and 83 control subjects. Internal consistency and test-retest reliability were evaluated. Content and clinical validity were studied, and the EAT-10 results were compared across patients and control groups. Results: The Arabic EAT-10 showed excellent internal consistency (Cronbach's α = 0.92). Also, good test-retest reliability was found for the total scores of the Arabic EAT-10 (intraclass correlation = 0.73). There was a significant difference in Arabic EAT-10 scores between the oropharyngeal dysphagia group and the control group (p < 0.001). Conclusion: This study demonstrated that the Arabic EAT-10 is a valid tool that can be used for screening of dysphagia-related problems in an Arabic-speaking population.

In this paper, we propose a voice pathology detection and classification method using an interlaced derivative pattern (IDP), which involves an n-th order directional derivative, on a spectro-temporal description of a glottal source excitation signal. It is shown previously that directional information is useful to detect pathologies due to its encoding ability along time, frequency, and timefrequency axes. The IDP, being an n-th order derivative, is capable of describing more information than a first order derivative pattern by combining all the directional information into one. In the IDP, first-order derivatives are calculated in four directions, and these derivatives are thresholded with the center value of each directional channel to produce the final IDP. A support vector machine is used as a classification technique. Experiments are conducted using three different databases, which are the Massachusetts Eye and Ear Infirmary database, Saarbrucken Voice Database, and Arabic Voice Pathology Database. Experimental results show that the IDP based features give higher accuracy than that using other related features in all the three databases. The accuracies using cross-databases are also high using the IDP features.

A voice disorder database is an essential element in doing research on automatic voice disorder detection and classification. Ethnicity affects the voice characteristics of a person, and so it is necessary to develop a database by collecting the voice samples of the targeted ethnic group. This will enhance the chances of arriving at a global solution for the accurate and reliable diagnosis of voice disorders by understanding the characteristics of a local group. Motivated by such idea, an Arabic voice pathology database (AVPD) is designed and developed in this study by recording three vowels, running speech, and isolated words. For each recorded samples, the perceptual severity is also provided which is a unique aspect of the AVPD. During the development of the AVPD, the shortcomings of different voice disorder databases were identified so that they could be avoided in the AVPD. In addition, the AVPD is evaluated by using six different types of speech features and four types of machine learning algorithms. The results of detection and classification of voice disorders obtained with the sustained vowel and the running speech are also compared with the results of an English-language disorder database, the Massachusetts Eye and Ear Infirmary (MEEI) database.

The experimental results demonstrate a clear difference in the performance of the MDVP parameters using these databases. The highly ranked parameters also differed from one database to another. The best accuracies were obtained by using the three highest ranked MDVP parameters arranged according to the Fisher discrimination ratio: these accuracies were 99.68%, 88.21%, and 72.53% for the Saarbruecken Voice Database, the Massachusetts Eye and Ear Infirmary database, and the Arabic voice pathology database, respectively.

Background The following position statement from the Union of the European Phoniatricians, updated on 25th May 2020 (superseding the previous statement issued on 21st April 2020), contains a series of recommendations for phoniatricians and ENT surgeons who provide and/or run voice, swallowing, speech and language, or paediatric audiology services. Objectives This material specifically aims to inform clinical practices in countries where clinics and operating theatres are reopening for elective work. It endeavours to present a current European view in relation to common procedures, many of which fall under the aegis of aerosol generating procedures. Conclusion As evidence continues to build, some of the recommended practices will undoubtedly evolve, but it is hoped that the updated position statement will offer clinicians precepts on safe clinical practice.