MFCC-Based Modeling of L1 Influence in L2 English Pronunciation: A Reproducible Methodological Pipeline

This technical documentation accompanies the study Modeling L1 Influence in L2 English Pronunciation: An MFCC-Based Explainable Machine Learning Approach and provides a fully reproducible, Python-based implementation of the complete analytical pipeline. The goal of this repository is to promote transparency, replicability, and scholarly rigor in modeling L1-induced variation in L2 English speech using Mel-Frequency Cepstral Coefficients (MFCCs) and interpretable machine learning techniques.