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Neyshekar corpus released for Persian speech recognition

By PulseAugur Editorial · [1 sources] ·

A new open Persian read-speech corpus named Neyshekar has been released, containing over 62,000 recordings totaling nearly 100 hours. This corpus is designed to cover formal and informal Persian, named entities, and longer utterances, with contributions from 190 individuals. The data was processed using the 'shekar' library for normalization and includes detailed characteristics such as recording load and signal quality. Evaluations show that Neyshekar significantly reduces Word Error Rate (WER) and Character Error Rate (CER) for automatic speech recognition architectures like Whisper and XLS-R compared to existing Persian datasets. AI

IMPACT Provides a valuable resource for improving Persian language ASR systems, potentially leading to better voice interfaces and transcription services.

RANK_REASON The item is an academic paper detailing a new dataset for speech recognition. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Neyshekar corpus released for Persian speech recognition

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The item is an academic paper detailing a new dataset for speech recognition. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Ahmad Amirivojdan, Farzad Nadiri, Abolfazl Alizadeh, Shaghayegh Yaraghi ·

    Neyshekar: An Open Persian Read-Speech Corpus for Automatic Speech Recognition

    arXiv:2609.14542v1 Announce Type: new Abstract: 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 prov…

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