3rd International Conference on NLP & AI (NLPAI 2025)

<!DOCTYPE html> <html> <head>  <link href="https://fonts.googleapis.com/icon?family=Material+Icons" rel="stylesheet"> <link href="https://fonts.googleapis.com/css?family=Roboto+Condensed" rel="stylesheet">  <link type="text/css" rel="stylesheet" href="css/materialize.min.css" media="screen,projection" /> <link rel="stylesheet" href="https://use.fontawesome.com/releases/v5.0.13/css/all.css" integrity="sha384-DNOHZ68U8hZfKXOrtjWvjxusGo9WQnrNx2sqG0tfsghAvtVlRW3tvkXWZh58N9jp" crossorigin="anonymous"> <link type="text/css" rel="stylesheet" href="css/main.css" /> <meta charset="UTF-8">  <meta name="viewport" content="width=device-width, initial-scale=1.0" /> <title> 3rd International Conference on NLP & AI (NLPAI 2025) </title> <link rel="icon" type="image/ico" href="img/logo.ico"> </head> <body>  <header class="main-header"> <nav class="transparent"> <div class="container"> <div class="nav-wrapper"> <a href="#" class="brand-logo">NLPAI </a> <a href="#" data-activates="mobile-nav" class="button-collapse"> <i class="fa fa-bars"></i> </a> <ul class="right hide-on-med-and-down"> <li> <a href="index">HOME</a> </li> <li> <a href="papersubmission">PAPER SUBMISSION</a> </li> <li> <a href="committee">PROGRAM COMMITTEE</a> </li> <li> <a class="active-link" href="#">ACCEPTED PAPERS</a> </li> <li> <a href="contact">CONTACT US</a> </li> </ul> <ul class="side-nav grey darken-1 white-text" id="mobile-nav"> <h4 class="center">NLPAI 2025</h4> <li> <div class="divider"></div> </li> <li> <a href="index"> <i class="fa fa-home white-text"></i>Home </a> </li> <li> <a href="papersubmission"> <i class="fa fa-user white-text"></i>Paper Submission </a> </li> <li> <a href="committee"> <i class="fa fa-user white-text"></i>Program Committee </a> </li> <li> <a class="active-link" href="papers"> <i class="fa fa-newspaper white-text"></i>Accepted Papers </a> </li> <li> <a href="contact"> <i class="fa fa-phone white-text"></i>Contact Us </a> </li> <li> <div class="divider"></div> </li> <li> <a href="/submission/index.php" target="blank" class="btn grey waves-effect waves-light">Paper Submission</a> </li> </ul> </div> </div> </nav>  <div class="showcase container"> <div class="row"> <div class="col s12 m10 offset-m1 center grey-text text-darken-3"> <h5>Welcome to NLPAI 2025</h5> <h2>3<sup>rd</sup> International Conference on NLP & AI (NLPAI 2025) </h2> <p>March 28 ~ 29, 2025, Virtual Conference</p> <br> <br> </div> </div> </div> </header> <section class="section section-icons "> <div class="container"> <div class="row"> <div class="col s12 m12"> <div class="card-panel grey darken-2 z-depth-3 white-text center"> <i class="fa fa-paper-plane fa-3x"></i> <h5>Accepted Papers</h5> </div> </div> <div class="col s12 m12"> <div class="card-panel white z-depth-3 "> <h6 style="color:black;font-family:classic wide,sans-cserif;font-size:20px"><b>The Impact of Artificial Intelligence on Project Managers and Scrum Masters: A Review and Evaluation Study</b></h6> <p style="color:black;text-align:justify;font-size: 15px;">Heidrich Vicci, College of Business Florida International University, USA </p> <h6 style="color:black;font-family:classic wide,sans-serif;"><b>ABSTRACT</b></h6> <p style="color:black;text-align:justify;">Artificial intelligence has taken a central role in various industries in the past decade as the importance of data has been at the forefront of all business decisions and policies. However, the increasing introduction of AI is proposed to alter entire project management enterprises as online platforms and applications have arisen, providing users with AI emotional intelligence, project management, and organizational tools. Bots are able to create reports, provide analysis, and facilitate headway by generating prioritized tasks and delegating to individuals through teamwork recommendation engines. However, the potential for AI to completely automate project management and Scrum Master tasks and remove job opportunities has yet to be comprehensively discussed. (Auth et al.2021)(Najdawi and Shaheen2021)(Josyula et al.2023). </p> <h6 style="color:black;font-family:classic wide,sans-serif;"><b>Keywords</b></h6> <p style="color:black;text-align:justify;">Artificial Intelligence (AI), Scrum Master, Project Management (PM). </p> <br> <h6 style="color:black;font-family:classic wide,sans-cserif;font-size:20px"><b>Automatic Speech Synthesis for Arabic Language using the Generated Schemes Method</b></h6> <p style="color:black;text-align:justify;font-size: 15px;">Chegrani Lamari, Guerti Mhania, Boudraa Bachir, Algeria </p> <h6 style="color:black;font-family:classic wide,sans-serif;"><b>ABSTRACT</b></h6> <p style="color:black;text-align:justify;">The purpose of this work is to generate units of language using in the speech synthesis of Arabic language based on concepts of schemes to generate syllables of sequence of Arabic language. The aim of this study is to develop a spoken communication aid system for the visually impaired in the Arab world. We can generate basic units; verbs, names and particles. We can also generate all speech in different levels (syllable sequence, word sequence and sentence or text sequence) depend on different generated schemes. </p> <h6 style="color:black;font-family:classic wide,sans-serif;"><b>Keywords</b></h6> <p style="color:black;text-align:justify;">Text-to-speech; Arabic scheme; speech synthesis; concatenative synthesis; generated scheme; generation of Sequence. </p> <br> <h6 style="color:black;font-family:classic wide,sans-cserif;font-size:20px"><b>Arabic Online Metaphor Sentiment Classification using Semantic Information</b></h6> <p style="color:black;text-align:justify;font-size: 15px;">Israa Alsiyat, School of Computing and Communications, Lancaster University, and College of Science, Northern Border University, UK </p> <h6 style="color:black;font-family:classic wide,sans-serif;"><b>ABSTRACT</b></h6> <p style="color:black;text-align:justify;">In this paper, I discuss the testing of the Arabic Metaphor Corpus (AMC) [1] using a newly designed automatic tools for sentiment classification for AMC based on semantic tags. The tool incorporates semantic emotional tags for sentiment classification. I evaluate the tool using standard methods, which are F-score, recall and precision. The method is to show the impact of Arabic online metaphors on sentiment through the newly designed tools. To the best of our knowledge, this is the first approach to conduct sentiment classification for Arabic metaphors using semantic tags to find the impact of metaphor. </p> <h6 style="color:black;font-family:classic wide,sans-serif;"><b>Keywords</b></h6> <p style="color:black;text-align:justify;">Arabic metaphor, sentiment analysis, NLP , Arabic semantic tagger. </p> <br> <h6 style="color:black;font-family:classic wide,sans-cserif;font-size:20px"><b>Synthetic Personas: Enhancing Demographic Response Simulation Through Large Language Models and Genetic Algorithms</b></h6> <p style="color:black;text-align:justify;font-size: 15px;">Morten Grundetjern, Per Arne Andersen, and Morten Goodwin, University of Agder, Grimstad, Norway </p> <h6 style="color:black;font-family:classic wide,sans-serif;"><b>ABSTRACT</b></h6> <p style="color:black;text-align:justify;">Understanding diverse demographic groups presents a significant challenge in market research. In this paper, we introduce a novel system that integrates large language models with genetic algorithms to create synthetic personas capable of generating feedback that approximates real-world human responses. Our experimental evaluation demonstrates that synthetic personas not only exhibit age-differentiated technology usage patterns consistent with documented trends but also benefit from genetic algorithm optimization, which improves response accuracy from 60.4% to 78.5% on training questions and from 62.6% to 68.8% on hidden questions鈥攐utperforming human estimators. Moreover, the optimized personas achieve a 51.1% better correspondence with actual income distributions compared to random profiles. This approach makes it possible to rapidly generate feedback without requiring participants, facilitates iterative follow-ups, and systematically enhances demographic representativeness. </p> <h6 style="color:black;font-family:classic wide,sans-serif;"><b>Keywords</b></h6> <p style="color:black;text-align:justify;">Synthetic Personas Large Language Models Genetic Algorithms Demographic Modeling Survey Response Simulation. </p> <br> </div> </div> </div> </div> </section>   <footer class="page-footer grey lighten-1"> <div class="container"> <div class="row"> <div class="col s12 m6"> <h5 class="grey-text lighten-3"> <font color="#FFF">Contact Us</font> </h5> <a href="mailto:nlpai@nlpai2025.org" style="color:#000">nlpai@nlpai2025.org</a> </div> </div> </div> <div class="footer-copyright grey darken-2"> <div class="container center"> Copyright © NLPAI 2025 </div> </div> </footer>  <script type="text/javascript" src="https://code.jquery.com/jquery-3.2.1.min.js"></script> <script type="text/javascript" src="js/materialize.min.js"></script> <script> $(document).ready(function () { // Custom JS & jQuery here $('.button-collapse').sideNav(); }); </script> </body> </html>

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3rd International Conference on NLP & AI (NLPAI 2025)