ParsVoice: A Large-Scale Multi-Speaker Persian Speech Corpus

1,804 hours of high-quality Persian speech data designed for text-to-speech applications. The dataset, created by MohammadJRanjbar, addresses a gap in Persian speech technology by providing speaker diversity and audio quality comparable to major English corpora. It was last updated on the platform in October 2025.

Use Cases

• Train text-to-speech models based on the described high-quality, multi-speaker audio corpus.
• Benchmark Persian speech synthesis systems based on the large-scale, 1,804-hour dataset.
• Develop voice cloning or multi-speaker TTS systems based on the described speaker diversity.

Strengths

• Contains 1,804 hours of speech data, making it a large-scale resource.
• Designed specifically for Persian text-to-speech, addressing a described gap in the language's resources.
• Claims high audio quality and speaker diversity comparable to major English corpora.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and file formats are unknown, which may limit suitability assessment.
• Data may reflect biases inherent to its source collection methods, which are not detailed.

Provenance

Source

MohammadJRanjbar

Freshness

Last updated 2025-10-15 11:13:02.

Geography

Persian language focus.