Egyptian Arabic Speech Recognition Data for Food Ordering

Egyptian Arabic STT Dataset is a synthetic speech dataset containing 50 samples totaling 85.2 seconds of audio. The samples were generated by the Synthetic Egyptian Speech Data Pipeline and have been human-reviewed and quality-validated using Whisper ASR, achieving an average WER of 0.4136 and CER of 0.1642. The dataset focuses on the topic of food ordering.

Use Cases

• Training speech-to-text models for Egyptian Arabic based on the validated dialect samples.
• Benchmarking ASR model performance on synthetic speech data based on the provided WER and CER metrics.
• Developing voice interfaces for food ordering applications based on the described topic focus.

Strengths

• All 50 samples have been validated for dialect authenticity.
• Quality metrics are provided, including an average Word Error Rate (WER) of 0.4136 and Character Error Rate (CER) of 0.1642.
• Dataset has a specific, narrow topical focus on food ordering.

Limitations

• The dataset is very small, containing only 50 samples with a total duration of 85.2 seconds.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is synthetic, which may not fully capture the characteristics of natural speech.

Provenance

Source

Khaledtelbahnasy via Hugging Face.

Collection Method

Synthetically generated by the Synthetic Egyptian Speech Data Pipeline, followed by human review and Whisper ASR validation.

Freshness

Last updated 2026-05-12 21:20:17; freshness should be verified.

Geography

Egyptian Arabic dialect.