Farsi YouTube Audio Chunks for Speech Recognition

Over 300 hours of Farsi speech data chunked into 30-second segments, derived from YouTube videos. The dataset was created by pourmand1376 and last updated on March 7, 2024. It is intended for training and testing automatic speech recognition models.

Use Cases

• Train automatic speech recognition models based on Farsi audio chunks.
• Benchmark ASR model performance on a dedicated test split.
• Fine-tune pre-trained speech models for the Farsi language.
• Analyze acoustic patterns in Farsi speech from online video sources.

Strengths

• Contains over 300 hours of Farsi speech data.
• Audio is pre-processed into consistent 30-second chunks.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

YouTube videos, via a Kaggle dataset.

Collection Method

Generated and chunked from source videos.

Freshness

Last updated 2024-03-07 09:33:17; freshness should be verified.