Abstract: Waray-Waray, also known as Winaray or Lineyte-Samarnon, is one of the most widely spoken Bisayan languages, primarily spoken throughout Samar, the Eastern Visayas region, and certain areas of Leyte Island. The native speakers of this language are referred to as Waray or Samarnon. As one of the primary regional languages in use in Visayas media and education, Waray plays a vital role in promoting inclusive and equitable language learning. In line with the United Nations Sustainable Development Goal 4 (Quality Education), this study seeks to create an alternative modular learning approach that strengthens the implementation of the Mother Tongue-Based Multilingual Education (MTB-MLE) program. The proposed Module-Based MTB-MLE Waray Language Learning System, which incorporates a Genetic Algorithm and a Hidden Markov Model (HMM), is intended to improve reading fluency and comprehension skills among primary learners. The learning modules are aligned with the MTB-MLE curriculum for Grades 1-3, ensuring accessibility, inclusivity, and cultural relevance. This paper presents the system's conceptual framework, processes, and testing procedures. The framework incorporates feature extraction methods, including Mel-Frequency Cepstral Coefficients (MFCC) for speech analysis and employs Hidden Markov Models for probabilistic language modeling. Additionally, the Genetic Algorithm is applied for speech comparison and optimization. Testing involves recordings of representative words and phrases from MTB-MLE modules spoken by native Waray speakers, serving as reference data. Through this study, the authors aim to contribute to SDG 4 by promoting inclusive, equitable, and high-quality language education that empowers both learners and educators in linguistically diverse regions of the Philippines.