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        <title>SUH_ASR@LT-EDI-ACL2022: Transformer based Approach for Speech Recognition for Vulnerable Individuals in Tamil</title>
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            <namePart type="given">Bharathi</namePart>
            <namePart type="given">Raja</namePart>
            <namePart type="family">Chakravarthi</namePart>
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        <name type="personal">
            <namePart type="given">Kalika</namePart>
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    <abstract>An Automatic Speech Recognition System is developed for addressing the Tamil conversational speech data of the elderly people andtransgender. The speech corpus used in this system is collected from the people who adhere their communication in Tamil at some primary places like bank, hospital, vegetable markets. Our ASR system is designed with pre-trained model which is used to recognize the speechdata. WER(Word Error Rate) calculation is used to analyse the performance of the ASR system. This evaluation could help to make acomparison of utterances between the elderly people and others. Similarly, the comparison between the transgender and other people isalso done. Our proposed ASR system achieves the word error rate as 39.65%.</abstract>
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%0 Conference Proceedings
%T SUH_ASR@LT-EDI-ACL2022: Transformer based Approach for Speech Recognition for Vulnerable Individuals in Tamil
%A S, Suhasini
%A B, Bharathi
%Y Chakravarthi, Bharathi Raja
%Y Bharathi, B.
%Y McCrae, John P.
%Y Zarrouk, Manel
%Y Bali, Kalika
%Y Buitelaar, Paul
%S Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F s-b-2022-suh
%X An Automatic Speech Recognition System is developed for addressing the Tamil conversational speech data of the elderly people andtransgender. The speech corpus used in this system is collected from the people who adhere their communication in Tamil at some primary places like bank, hospital, vegetable markets. Our ASR system is designed with pre-trained model which is used to recognize the speechdata. WER(Word Error Rate) calculation is used to analyse the performance of the ASR system. This evaluation could help to make acomparison of utterances between the elderly people and others. Similarly, the comparison between the transgender and other people isalso done. Our proposed ASR system achieves the word error rate as 39.65%.
%R 10.18653/v1/2022.ltedi-1.23
%U https://aclanthology.org/2022.ltedi-1.23
%U https://doi.org/10.18653/v1/2022.ltedi-1.23
%P 177-182

Markdown (Informal)

[SUH_ASR@LT-EDI-ACL2022: Transformer based Approach for Speech Recognition for Vulnerable Individuals in Tamil](https://aclanthology.org/2022.ltedi-1.23) (S & B, LTEDI 2022)

• SUH_ASR@LT-EDI-ACL2022: Transformer based Approach for Speech Recognition for Vulnerable Individuals in Tamil (S & B, LTEDI 2022)

ACL

• Suhasini S and Bharathi B. 2022. SUH_ASR@LT-EDI-ACL2022: Transformer based Approach for Speech Recognition for Vulnerable Individuals in Tamil. In Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion, pages 177–182, Dublin, Ireland. Association for Computational Linguistics.