Gujarati Podcast Audio Collection with 2,471 Hours of Processed Speech

A large-scale collection of 2,471 hours of processed Gujarati podcast audio recordings, part of a broader multilingual corpus of 57,568 hours across 12 languages. The dataset was created by InfoBayAI and last updated in June 2026. It captures real-world interactions across diverse topics and formats to support speech AI development.

Use Cases

• Training automatic speech recognition (ASR) models based on natural Gujarati speech patterns.
• Developing text-to-speech (TTS) systems based on speaker variability and authentic podcast environments.
• Building multilingual speech models based on the dataset's coverage of 12 languages.
• Researching conversational AI based on real-world podcast interactions and diverse topics.

Strengths

• Contains 2,471 hours of processed Gujarati audio, a substantial volume for model training.
• Part of a larger multilingual corpus totaling 57,568 hours across 12 languages.
• Captures real-world interactions and natural speech patterns, as described.

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.
• The specific file formats, size, and exact row count are unknown.

Provenance

Source

InfoBayAI via Hugging Face.

Collection Method

Collection and processing of podcast audio recordings, as described.

Freshness

Last updated 2026-06-03 05:31:22; freshness should be verified.