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.本数据集包含源自儿童语音录音的结构化声学-韵律特征向量，用于发育性语言评估。所提取的特征涵盖1~13阶梅尔频率倒谱系数（Mel-Frequency Cepstral Coefficients，MFCC）、基频（F0）、抖动、闪烁、谐波信噪比、频谱质心、语速及时域参数。本数据集可用于采用主成分分析（Principal Component Analysis，PCA）与模糊C均值（Fuzzy C-Means，FCM）开展的降维与聚类分析任务。所有特征均以表格格式组织，适配机器学习与统计建模工作。