@inproceedings{b-etal-2022-findings-shared,
title = "Findings of the Shared Task on Speech Recognition for Vulnerable Individuals in {T}amil",
author = "B, Bharathi and
Chakravarthi, Bharathi Raja and
Cn, Subalalitha and
N, Sripriya and
Pandian, Arunaggiri and
Valli, Swetha",
editor = "Chakravarthi, Bharathi Raja and
Bharathi, B and
McCrae, John P and
Zarrouk, Manel and
Bali, Kalika and
Buitelaar, Paul",
booktitle = "Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion",
month = may,
year = "2022",
address = "Dublin, Ireland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.ltedi-1.52",
doi = "10.18653/v1/2022.ltedi-1.52",
pages = "339--345",
abstract = "This paper illustrates the overview of the sharedtask on automatic speech recognition in the Tamillanguage. In the shared task, spontaneousTamil speech data gathered from elderly andtransgender people was given for recognitionand evaluation. These utterances were collected from people when they communicatedin the public locations such as hospitals, markets, vegetable shop, etc. The speech corpusincludes utterances of male, female, and transgender and was split into training and testingdata. The given task was evaluated using WER(Word Error Rate). The participants used thetransformer-based model for automatic speechrecognition. Different results using differentpre-trained transformer models are discussedin this overview paper.",
}
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<abstract>This paper illustrates the overview of the sharedtask on automatic speech recognition in the Tamillanguage. In the shared task, spontaneousTamil speech data gathered from elderly andtransgender people was given for recognitionand evaluation. These utterances were collected from people when they communicatedin the public locations such as hospitals, markets, vegetable shop, etc. The speech corpusincludes utterances of male, female, and transgender and was split into training and testingdata. The given task was evaluated using WER(Word Error Rate). The participants used thetransformer-based model for automatic speechrecognition. Different results using differentpre-trained transformer models are discussedin this overview paper.</abstract>
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%0 Conference Proceedings
%T Findings of the Shared Task on Speech Recognition for Vulnerable Individuals in Tamil
%A B, Bharathi
%A Chakravarthi, Bharathi Raja
%A Cn, Subalalitha
%A N, Sripriya
%A Pandian, Arunaggiri
%A Valli, Swetha
%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 b-etal-2022-findings-shared
%X This paper illustrates the overview of the sharedtask on automatic speech recognition in the Tamillanguage. In the shared task, spontaneousTamil speech data gathered from elderly andtransgender people was given for recognitionand evaluation. These utterances were collected from people when they communicatedin the public locations such as hospitals, markets, vegetable shop, etc. The speech corpusincludes utterances of male, female, and transgender and was split into training and testingdata. The given task was evaluated using WER(Word Error Rate). The participants used thetransformer-based model for automatic speechrecognition. Different results using differentpre-trained transformer models are discussedin this overview paper.
%R 10.18653/v1/2022.ltedi-1.52
%U https://aclanthology.org/2022.ltedi-1.52
%U https://doi.org/10.18653/v1/2022.ltedi-1.52
%P 339-345
Markdown (Informal)
[Findings of the Shared Task on Speech Recognition for Vulnerable Individuals in Tamil](https://aclanthology.org/2022.ltedi-1.52) (B et al., LTEDI 2022)
ACL