YodaLingua-Arabic: 730 Hours of Speech for Text-to-Speech and ASR

260,162 audio-transcription pairs totaling 730 hours of speech data from 13,290 distinct speakers. This Arabic portion of the YodaLingua collection is designed for training text-to-speech and automatic speech recognition models. The dataset was created by Thomcles and was last updated on May 12, 2026.

Use Cases

• Train text-to-speech models based on the high-quality, well-aligned audio-text pairs.
• Develop automatic speech recognition systems based on the 730 hours of transcribed speech.
• Fine-tune voice cloning or speech synthesis models based on data from 13,290 distinct speakers.
• Benchmark speech processing algorithms for the Arabic language based on the large-scale, multilingual collection.

Strengths

• Contains 260,162 individual audio clips, providing a substantial volume of training examples.
• Offers 730 total hours of transcribed speech, enabling training of data-intensive models.
• Includes data from 13,290 distinct speakers, which likely contributes to speaker diversity.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.
• Last updated 2026-05-12 19:43:27; freshness should be verified.

Provenance

Source

huggingface

Freshness

Last updated 2026-05-12 19:43:27.