The lack of impaired speech data hinders advancements in the development of inclusive speech technologies, particularly in low-resource languages such as Akan. To address this gap, this study presents a curated corpus of speech samples from native Akan speakers with speech impairment. The dataset comprises of 50.01 hours of audio recordings cutting across four classes of impaired speech namely stammering, cerebral palsy, cleft palate, and stroke induced speech disorder. Recordings were done in controlled supervised environments were participants described pre-selected images in their own words. The resulting dataset is a collection of audio recordings, transcriptions, and associated metadata on speaker demographics, class of impairment, recording environment and device. The dataset is intended to support research in low-resource automatic disordered speech recognition systems and assistive speech technology.

翻译：缺乏障碍语音数据阻碍了包容性语音技术的发展，特别是在阿坎语等低资源语言中。为填补这一空白，本研究构建了一个来自阿坎语母语障碍人士的语音样本库。该数据集包含50.01小时的音频录音，涵盖四种障碍语音类型：口吃、脑瘫、腭裂及中风所致言语障碍。录音在受控监督环境下进行，参与者用自身语言描述预先选定的图像。最终数据集包含音频录音、转写文本，以及说话人人口统计信息、障碍类别、录音环境与设备等元数据。本数据集旨在支持低资源自动障碍语音识别系统及辅助语音技术的研究。