supplementary_dataset_hybrid_pca_fcm_v1

This dataset contains structured acoustic–prosodic feature vectors derived from pediatric speech recordings for developmental language assessment. Extracted features include MFCC (1–13), fundamental frequency (F0), jitter, shimmer, harmonic-to-noise ratio, spectral centroid, speech rate, and temporal parameters. The dataset is intended for dimensionality reduction and clustering analysis using Principal Component Analysis (PCA) and Fuzzy C-Means (FCM). All features are organized in a tabular format suitable for machine learning and statistical modeling.