Bosnian Vowels Analysis Using Formant Frequencies

One way for analysis of vowels in any language is an analysis using formant frequency analysis. The Bosnian language has five vowels and those are a, e, i, o, u. The research was conducted in such a way that words with a minimum of two identical vowels per word were selected for each vowel. Several samples were then collected that recorded each of the words, and then those words were analyzed in PRAAT software. The total number of samples was 1050, twenty-one subjects were included, twelve females and nine males. Each of them recorded ten words for each of five vowels, therefore fifty words by each subject. The outcomes are based on related articles and dissertations, recognition, and analysis of vowels. Recognition was based on the statement, reading the literature, that each person has a narrow band of F4 formant values that should identify the person. And the analysis part was done by comparing formant values. Also, the work was based on gender differences for this analysis, as well as some other small observations, for example, the difference between native and other speakers of the Bosnian language

Deep Transfer Learning for Food Recognition

Food Recognition is an essential topic in the area of computer of its target applications is to avoid achieving a cashier at the dining place. In this paper, we investigate the application of Deep Transfer Learning for food recognition. We fine-tune three well learning models namely; AlexNet, GoogleNet, and Vgg16. The fine tuning procedure depends on removing the last three layers of each model and adds another five new layers. The training and validation of each model conducted through food a dataset collected from our university's canteen. The dataset contains 39 food types, 20 images for each type. The fine-tuned models show similar training and validation performance and achieved 100% accuracy over the small-scale dataset