TantaArabNLP at KSAA-2026 Task 2: Adapting CATT-Whisper for Arabic Speech Dictation with Automatic Diacritization
Year: 2026
Type: conference-paper
Abstract: We present our submission to the KSAA-2026 Shared Task (Subtask 2): Automatic Diacritization of Speech Dictation.Building upon the CATT-Whisper multimodal architecture, which fuses representations from a pre-trained CATT text encoder and the Whisper speech encoder, we fine-tune the model end-to-end on the official shared task training data.To further enhance performance on speech-dictated Arabic text, we apply careful post-processing to the model outputs.Our best submission achieves a Diacritic Error Rate (DER) of 7.04, a Word Error Rate (WER) of 24.39, and a Sentence Error Rate (SER) of 71.65 on the hidden test set, securing 2nd place in the competition.These results demonstrate the effectiveness of adapting a strong multimodal baseline to the speech-aware diacritization setting and highlight the value of task-specific fine-tuning and output refinement for bridging the gap between spoken transcripts and fully diacritized Arabic text.
Institution: Tanta University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7166580275