ArDSS: An Arabic Down Syndrome Speech Corpus

Abstract

Down syndrome (DS) is associated with characteristic speech impairments, yet Arabic resources remain limited. This paper introduces ArDSS, an annotated Arabic speech corpus of DS speech for acoustic analysis and Automatic Speech Recognition (ASR) research. Recordings were collected from 13 Arabic-speaking children with DS (6 males, 7 females; ages 5–17) in Saudi Arabia using a clinically guided set of 100 phonetically diverse isolated words, captured in 3–4 sessions per participant under controlled conditions. Following quality control and segmentation, ArDSS comprises 5,509 utterances (16 kHz, 16-bit WAV) totaling 14.6 hours. Each utterance is linked to XML metadata and attempt-level annotations, and a standardized pipeline extracts fundamental frequency, formants (F1–F3), and voice-quality measures (harmonics-to-noise ratio, jitter, shimmer) after feature-validity screening, yielding 3,279 productions with complete acoustic profiles. Corpus analyses indicate substantial inter-speaker variability and recurrent Arabic-relevant pronunciation patterns, including liquid substitution, emphatic neutralization, cluster reduction, and affricate simplification. ArDSS provides a foundational resource for Arabic clinical phonetics and for developing DS-aware ASR and assistive applications.