Synthetic and Augmented Dysarthric Speech Corpus

Synthetic-dysarthric-speech is a dataset containing artificially generated and augmented speech samples simulating dysarthria, a motor speech disorder. It is intended for developing robust automatic speech recognition and semantic understanding systems. The dataset's creator, size, and update date are not specified.

Use Cases

• Training ASR models to recognize dysarthric speech patterns using synthetic audio samples.
• Benchmarking the robustness of semantic understanding models against atypical speech data.
• Augmenting existing speech datasets with synthetic dysarthric variations to improve model generalization.

Strengths

• Dataset is specifically designed for a niche and important application in accessible speech technology.
• Focuses on synthetic and augmented data, which can be generated at scale for model training.

Limitations

• The synthetic nature of the data may not fully capture the acoustic variability of real dysarthric speech.
• Dataset size, sample count, and speaker diversity are unknown, limiting assessment of its scope.

Provenance

Collection Method

Synthetic generation and augmentation of speech samples to simulate dysarthria.