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        <title>Towards Unified Processing of Perso-Arabic Scripts for ASR</title>
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        <namePart type="given">Srihari</namePart>
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        <namePart type="family">Devarakonda</namePart>
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        <namePart type="given">Harinie</namePart>
        <namePart type="family">Sivaramasethu</namePart>
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            <title>Proceedings of the 1st Workshop on NLP for Languages Using Arabic Script</title>
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            <namePart type="given">Mo</namePart>
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    <abstract>Automatic Speech Recognition (ASR) systems for morphologically complex languages like Urdu, Persian, and Arabic face unique challenges due to the intricacies of Perso-Arabic scripts. Conventional data processing methods often fall short in effectively handling these languages’ phonetic and morphological nuances. This paper introduces a unified data processing pipeline tailored specifically for Perso-Arabic languages, addressing the complexities inherent in these scripts. The proposed pipeline encompasses comprehensive steps for data cleaning, tokenization, and phonemization, each of which has been meticulously evaluated and validated by expert linguists. Through expert-driven refinements, our pipeline presents a robust foundation for advancing ASR performance across Perso-Arabic languages, supporting the development of more accurate and linguistically informed multilingual ASR systems in future.</abstract>
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%0 Conference Proceedings
%T Towards Unified Processing of Perso-Arabic Scripts for ASR
%A Bandarupalli, Srihari
%A Akkiraju, Bhavana
%A Devarakonda, Sri Charan
%A Sivaramasethu, Harinie
%A Narasinga, Vamshiraghusimha
%A Vuppala, Anil
%Y El-Haj, Mo
%S Proceedings of the 1st Workshop on NLP for Languages Using Arabic Script
%D 2025
%8 January
%I Association for Computational Linguistics
%C Abu Dhabi, UAE
%F bandarupalli-etal-2025-towards
%X Automatic Speech Recognition (ASR) systems for morphologically complex languages like Urdu, Persian, and Arabic face unique challenges due to the intricacies of Perso-Arabic scripts. Conventional data processing methods often fall short in effectively handling these languages’ phonetic and morphological nuances. This paper introduces a unified data processing pipeline tailored specifically for Perso-Arabic languages, addressing the complexities inherent in these scripts. The proposed pipeline encompasses comprehensive steps for data cleaning, tokenization, and phonemization, each of which has been meticulously evaluated and validated by expert linguists. Through expert-driven refinements, our pipeline presents a robust foundation for advancing ASR performance across Perso-Arabic languages, supporting the development of more accurate and linguistically informed multilingual ASR systems in future.
%U https://aclanthology.org/2025.abjadnlp-1.3/
%P 23-28

Markdown (Informal)

[Towards Unified Processing of Perso-Arabic Scripts for ASR](https://aclanthology.org/2025.abjadnlp-1.3/) (Bandarupalli et al., AbjadNLP 2025)

• Towards Unified Processing of Perso-Arabic Scripts for ASR (Bandarupalli et al., AbjadNLP 2025)

ACL

• Srihari Bandarupalli, Bhavana Akkiraju, Sri Charan Devarakonda, Harinie Sivaramasethu, Vamshiraghusimha Narasinga, and Anil Vuppala. 2025. Towards Unified Processing of Perso-Arabic Scripts for ASR. In Proceedings of the 1st Workshop on NLP for Languages Using Arabic Script, pages 23–28, Abu Dhabi, UAE. Association for Computational Linguistics.