machine learning

Gender recognition from voice is a challenging problem in speech processing. This task involves extracting meaningful features from speech signals and classifying them into male or female categories. In this article, was implemented a gender recognition system using Python programming. I first recorded voice samples from both male and female speakers and extracted Mel-frequency cepstral coefficients (MFCC) as features. Then trained, a Support Vector Machine (SVM) classifier was on these features and evaluated its performance using accuracy, precision, recall, and F1-score metrics.

As a result of the research, one of the approaches to building an intelligent information system based on the recommendation of products to users with a solution to the cold start problem is described and modeled. The conducted research takes into account the advantages and disadvantages of the meth- ods, as well as their compatibility, when combining them, which is an important factor for the speed of the system and the efficiency of the algorithm.

This paper describes an information system for monitoring and analyzing reviews on social networks to form recommendations for the purchase of goods. This system is designed to be used by customers to speed up and facilitate the search for the necessary products on e-commerce resources. Successful selection of a quality product according to the desired criteria is extremely important, as it saves search time and customer money. Analyzing comments on the network, the information system recommends the product if there is a preponderance of positive feedback on it.

This article covers the problem of developing a control system for non-player characters in a multiplayer RPG. Commercial projects in the field of videogames and RPG (Role-Playing Game) projects in particular seldom use machine learning models for the implementation of character behaviour. The most common approach is to use primitive preprogrammed rules, or to implement a finite state machine. Such approaches ruin the immersion of playing with real creatures, since various predefined rules make the characters predictable.

Machine learning algorithms play an important role in analyzing complex data in research across various fields.  In this paper, we employ multiple regression algorithms and statistical techniques to investigate the relationship between objective and subjective quality of life indicators and reveal the key factors affecting happiness at the international level based on data from the Human Development Index and the World Happiness Index covering the period from 2015 to 2021.  The Pearson correlation analysis showed that happiness is related to the HDI score and GNI per capita.  The best-perfo

One of the important problems that urban residents suffer from is Traffic Congestion.  It makes their life more stressful, it impacts several sides including the economy: by wasting time, fuel and productivity.  Moreover, the psychological and physical health.  That makes road authorities required to find solutions for reducing traffic congestion and guaranteeing security and safety on roads.  To this end, detecting road users in real-time allows for providing features and information about specific road points.  These last are useful for road managers and also for road users about congeste

Machine learning algorithms have become very frequently used in natural language processing, notably sentiment analysis, which helps determine the general feeling carried within a text.  Among these algorithms, Support Vector Machines have proven powerful classifiers especially in such a task, when their performance is assessed through accuracy score and f1-score.  However, they remain slow in terms of training, thus making exhaustive grid-search experimentations very time-consuming.  In this paper, we present an observed pattern in SVM's accuracy, and f1-score approximated with a Lagrange

Many food contamination incidents have occurred during the last decade which has proven the failure of the food supply chain management system to track the food, money, and information movement within the food supply chain.  Many models have been established. This paper presents the design and implementation of the new model providing real-time data acquisition, monitoring, and storing on a tamper-proof blockchain of the main food supply movement.

Since the first computer, researchers always try to simulate human behave.  For Chatbots, one of the first goals is to interact with the user like a human using Natural Language.  For Health chatbots, another goal is as much important: be able to provide the correct answer to the user request.  Over Years, many health chatbots have been developed for many fields such as cancer, diagnosis orientation, psychiatrics, etc.