FUNDING
$425K
Seed Round Secured
Speech & Healthcare AI
FUNDING
Seed Round Secured
EXPERIMENTS
Training Runs
PRODUCTIVITY
Annotation Speed
WER
Word Error Rate
DATASET
Hours of Medical Audio
Where dialect barriers disrupt the clinical workflow
Documentation becomes a bottleneck when technology cannot keep pace with the natural spoken word. Every moment spent correcting a transcript is a moment stolen from a patient's bedside.
The Intellema Design Challenge
Healthcare professionals in Saudi Arabia face significant documentation burdens due to the limitations of standard speech recognition in medical settings. Existing systems often struggle to accurately capture specific regional dialects and complex clinical terminology during patient consultations.
The project required a custom ASR system tailored for Saudi Arabic dialects to convert spoken interactions into structured clinical notes. It focused on enhancing model robustness through synthetic data and audio cleaning to ensure reliable performance in high-stakes environments.
An ASR system specifically tailored for Saudi Arabic dialects within high-stakes medical environments.
Minimized documentation burden for healthcare professionals through automated transcription and processing.
Generation and integration of synthetic speech to bolster performance on low-resource datasets.
Enhanced system reliability using advanced audio cleaning techniques and self-supervised learning frameworks.
