Beyond the immediate content of speech, the voice can provide rich information about a speaker's demographics, including age and gender. Estimating a speaker's age and gender offers a wide range of applications, spanning from voice forensic analysis to personalized advertising, healthcare monitoring, and human-computer interaction. However, pinpointing precise age remains intricate due to age ambiguity. Specifically, utterances from individuals at adjacent ages are frequently indistinguishable. Addressing this, we propose a novel, end-to-end approach that deploys Mozilla's Common Voice dataset to transform raw audio into high-quality feature representations using Wav2Vec2.0 embeddings. These are then channeled into our self-attention-based convolutional neural network (CNN) model. To address age ambiguity, we evaluate the effects of different loss functions such as focal loss and Kullback-Leibler (KL) divergence loss. Additionally, we evaluate the accuracy of the estimation at different durations of speech. Experimental results from the Common Voice dataset underscore the efficacy of our approach, showcasing an accuracy of 87% for male speakers, 91% for female speakers and 89% overall accuracy, and an accuracy of 99.1% for gender prediction.
In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.
Background: Measuring the concentration of hepatitis B surface antigen (HbsAg) in HBV patients can be determined with immunoassay techniques. This study aimed to measure the HbsAg titers in chronic HBV patients and to assess its correlation with patients' ages, gender, and with the levels of liver enzymes and total serum bilirubin. Materials and Method: Fifty-eight chronic hepatitis B infected patients were enrolled in this study. Age and gender of the patients were recorded. HbsAg concentration was tested with automated Immunoanalyzer. The patients were also tested for ALT, AST, ALP, and TSB by automated chemistry analyzer. Results: All the chronic HBV patients have positive HBsAg titers above the negative cutoff (0.05U/L) with mea
... Show MoreThe process of evaluating data (age and the gender structure) is one of the important factors that help any country to draw plans and programs for the future. Discussed the errors in population data for the census of Iraqi population of 1997. targeted correct and revised to serve the purposes of planning. which will be smoothing the population databy using nonparametric regression estimator (Nadaraya-Watson estimator) This estimator depends on bandwidth (h) which can be calculate it by two ways of using Bayesian method, the first when observations distribution is Lognormal Kernel and the second is when observations distribution is Normal Kernel
... Show MoreHuman health was and still the most important problem and objective of all most researches. Finding out what causes in the decadence of healthiness of Iraqi population is our tendency in the present work, Uranium causing cancer that is affected by a correlation between age and gender of bladder cancer patients is studied in the present work. Mean of Uranium concentration (Uc) decreased with increasing age for all age group without dependency on gender. While, there is a wide dispersion in Mean Uc excretion between males and females, due to the effect of correlated gender with age, where female Mean Uc is maximum at age 50-69 year (2.355 µg/L), and it's higher than male Mean Uc (2.022 µg/L) in this age stage because of menopause, a
... Show MoreBackground: The Infraorbital foramen is an anatomical structure with an important location in the maxilla, position of foramen in maxillofacial area is necessary in clinical situation requiring regional nerve blocks that are performed in children undergoing facial surgeries to avoid injury to corresponding nerve. The aim of study was to determine the position of the Infraorbital foramen and to correlate Infraorbital foramen position with age and gender using computed tomography. Subjects, Materials, and Methods: The sample consist of prospective study for 50 Iraqi subjects (21 male and 29 female) with age ranged from (5-17) years. The examination was performed on Multi – Slice Spiral Tomography scanner in Al-Karakh General Hospital. Using
... Show MoreThis study aims to reveal the similarities and differences between Iraqi and Malay university learners and their genders in producing the supportive moves of criticism. To this end, 30 Iraqi and 30 Malay university learners have participated in this study. A Discourse Completion Test (DCT) and a Focus Group Interview (FGI) are conducted to elicit responses from the participants. Nguyen’s (2005) classification of criticism supportive moves is adapted to code the data. The data are analysed qualitatively and quantitatively. Overall, the findings unveil that both groups use similar categories of supportive moves, but Iraqis produce more of these devices than Malays in their criticisms. Although both females and males of both groups use id
... Show MoreThe use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow
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