Hindi Podcast Audio Dataset with 11,607 Hours of Processed Speech

InfoBayAI's Hindi Podcast Audio Dataset is a large-scale collection of 11,607 hours of processed Hindi podcast audio recordings. The full dataset contains 57,568 hours of processed audio across 12 languages, capturing real-world interactions across diverse topics and formats. It was last updated on June 8, 2026.

Use Cases

• Train Hindi speech recognition models based on the large volume of natural Hindi speech.
• Develop multilingual conversational AI systems based on the dataset's coverage of 12 languages.
• Study natural speech patterns and speaker variability based on the described preservation of authentic podcast environments.
• Benchmark audio processing pipelines based on the scale of processed audio recordings.

Strengths

• Contains 11,607 hours of processed Hindi podcast audio.
• Includes a total of 57,568 hours of processed audio across 12 languages.
• Designed to capture real-world interactions, natural speech patterns, and speaker variability.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and specific file formats are unknown, which may limit suitability assessment.
• Data may reflect topic and format bias inherent to the podcast sources.

Provenance

Source

InfoBayAI

Collection Method

Collection of processed podcast audio recordings, likely from various sources.

Freshness

Last updated 2026-06-08 04:28:31; freshness should be verified.