Nkugwa/wav2vec2-luganda-dysarthric-v7
Automatic Speech Recognition • 0.3B • Updated • 25
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This dataset provides 44.4 hours of Ugandan English speech recordings (8,137 samples) from 59 Ugandan speakers living with speech impairments. The participants represent a diversity of progressive, acquired and congenital aetiologies, including cerebral palsy, Parkinson's disease, multiple sclerosis, autism spectrum disorder, Down syndrome, stroke and stuttering.
This dataset includes a split into a training, test and development set. The splits were created avoiding any overlap on the speaker or phrase level. All speech recordings of this datasets have been transcribed by certified speech-language pathologists. Two passes of transcription have been made to ensure correctness. For this dataset, all recordings with low confidence transcriptions or disagreement between transcribers have been removed.
Additionally, this dataset contains speaker metadata such as gender, age, speech severity, impairment type, and underlying condition as assessed by certified speech-language pathologists. However, the dataset is fully anonymized, all potentially identifying information has been removed.
Recordings were gathered in Kampala and surrounding areas in 2025. Recordings are based on picture and text-based prompts, designed to capture natural, everyday speech patterns.
This dataset is part of a larger data collection initiative by UCL's Global Disability Innovation Hub as part of it's Centre for Digital Language Inclusion with support from UK International Development and Googe.org, and was collected in collaboration with Senses Hub, Kenya.
Users of this dataset must acknowledge our Terms & Conditions. We have anonymized the datasets to protect the speakers whose speech samples are contained in this dataset and it is strictly forbidden to attempt re-identify the speakers.
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