AbyatSpeech: Arabic Poetry Audio Recordings for Meter Classification

3,805 annotated audio recordings of classical Arabic poetry verses, totaling approximately 9 hours of data. The dataset was created by Dr. Abdul Kareem Saleh Al-Zahrani and published via Harvard Dataverse, with a last update in April 2026. Each sample is a single verse labeled according to one of 16 canonical Arabic poetic meters.

Use Cases

• Automatic poetry recognition based on recited audio recordings.
• Meter classification based on the 16 canonical Arabic poetic meter labels.
• Speech recognition for structured language based on controlled, high-quality audio samples.
• Arabic linguistic and prosody analysis based on annotated verse data.

Strengths

• 3,805 annotated audio samples provide a substantial corpus.
• Approximately 9 hours of total audio data with an average duration of around 9 seconds per sample.
• Recordings were captured under controlled laboratory conditions using professional-grade equipment, suggesting high acoustic quality.
• Each sample is labeled with one of 16 canonical Arabic poetic meters (Al-Buḥūr).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect bias inherent to the specific collection of classical Arabic poetry.

Provenance

Source

Harvard Dataverse, contributed by Dr. Abdul Kareem Saleh Al-Zahrani.

Collection Method

Recordings were captured under controlled laboratory conditions using professional-grade audio equipment.

Time Range

Temporal coverage is not specified in the provided metadata.

Freshness

Last updated 2026-04-06 01:49:41; freshness should be verified.

Geography

Spatial coverage is not specified in the provided metadata.