Neyshekar: An Open Persian Read-Speech Corpus for Automatic Speech Recognition
Neyshekar is presented as an open Persian read-speech corpus designed for coverage of both formal and informal language, named entities, and longer utterances. In version 6, 62,279 validated recordings totalling 99.02 hours are provided from 190 contributors, with 34,541 distinct recorded prompts. The prompt pool was assembled from human-written material, contextualised homographs, and reviewed language-model-generated text. Text entries were normalised with the shekar library, which supports both formal and informal Persian, and every submitted recording was reviewed against a common validation rubric. About 24% of released clips are classified as informal by an automatic classifier; the...
| Authors | Ahmad Amirivojdan, Farzad Nadiri, Abolfazl Alizadeh et al. |
|---|---|
| Primary category | cs.CL |
| Published | 13 September 2026 |
| Last updated at source | 13 September 2026 |
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- shekar-ai/NeyshekarDataset · cited by
Models and datasets referencing this paper
- shekar-ai/NeyshekarDataset
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