@inproceedings{r-gawde-etal-2024-shabdocchar,
title = "Shabdocchar: {K}onkani {W}ord{N}et Enrichment with Audio Feature",
author = "R. Gawde, Sunayana and
R. Parab, Shrikrishna and
Gawas, Jayram Ulhas and
Desai, Shilpa Neenad and
Pawar, Jyoti",
editor = "Lalitha Devi, Sobha and
Arora, Karunesh",
booktitle = "Proceedings of the 21st International Conference on Natural Language Processing (ICON)",
month = dec,
year = "2024",
address = "AU-KBC Research Centre, Chennai, India",
publisher = "NLP Association of India (NLPAI)",
url = "https://aclanthology.org/2024.icon-1.62/",
pages = "531--536",
abstract = "Konkani WordNet, also called Konkani Shabdamalem, was created as part of the Indradhanush WordNet Project Consortium between August 2010 and October 2013. Currently, the Konkani WordNet includes about 32,370 synsets and 37,719 unique words. There is a need to enhance the Konkani WordNet both quantitatively as well as qualitatively. In this paper we are presenting a Game-Based Crowdsourcing approach adopted by us to add audio feature to the Konkani WordNet which has resulted in an increase in the number of users using and getting exposed to the capabilities of the Konkani WordNet to aid in the Konkani language teaching-learning process as well as for creation of resources to initiate further research. Our work presented here has resulted in the creation of an audio corpus of 37,719 unique words which we have named as {\textquoteleft}Shabdocchar' within a short time span of four months covering five dialects of Konkani. We are confident that Shabdocchar will prove to be a very useful resource to support future research work on Dialects of Konkani and support voice-based search of words in the wordnet. This approach can be adopted to enhance other wordnets as well."
}
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<abstract>Konkani WordNet, also called Konkani Shabdamalem, was created as part of the Indradhanush WordNet Project Consortium between August 2010 and October 2013. Currently, the Konkani WordNet includes about 32,370 synsets and 37,719 unique words. There is a need to enhance the Konkani WordNet both quantitatively as well as qualitatively. In this paper we are presenting a Game-Based Crowdsourcing approach adopted by us to add audio feature to the Konkani WordNet which has resulted in an increase in the number of users using and getting exposed to the capabilities of the Konkani WordNet to aid in the Konkani language teaching-learning process as well as for creation of resources to initiate further research. Our work presented here has resulted in the creation of an audio corpus of 37,719 unique words which we have named as ‘Shabdocchar’ within a short time span of four months covering five dialects of Konkani. We are confident that Shabdocchar will prove to be a very useful resource to support future research work on Dialects of Konkani and support voice-based search of words in the wordnet. This approach can be adopted to enhance other wordnets as well.</abstract>
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%0 Conference Proceedings
%T Shabdocchar: Konkani WordNet Enrichment with Audio Feature
%A R. Gawde, Sunayana
%A R. Parab, Shrikrishna
%A Gawas, Jayram Ulhas
%A Desai, Shilpa Neenad
%A Pawar, Jyoti
%Y Lalitha Devi, Sobha
%Y Arora, Karunesh
%S Proceedings of the 21st International Conference on Natural Language Processing (ICON)
%D 2024
%8 December
%I NLP Association of India (NLPAI)
%C AU-KBC Research Centre, Chennai, India
%F r-gawde-etal-2024-shabdocchar
%X Konkani WordNet, also called Konkani Shabdamalem, was created as part of the Indradhanush WordNet Project Consortium between August 2010 and October 2013. Currently, the Konkani WordNet includes about 32,370 synsets and 37,719 unique words. There is a need to enhance the Konkani WordNet both quantitatively as well as qualitatively. In this paper we are presenting a Game-Based Crowdsourcing approach adopted by us to add audio feature to the Konkani WordNet which has resulted in an increase in the number of users using and getting exposed to the capabilities of the Konkani WordNet to aid in the Konkani language teaching-learning process as well as for creation of resources to initiate further research. Our work presented here has resulted in the creation of an audio corpus of 37,719 unique words which we have named as ‘Shabdocchar’ within a short time span of four months covering five dialects of Konkani. We are confident that Shabdocchar will prove to be a very useful resource to support future research work on Dialects of Konkani and support voice-based search of words in the wordnet. This approach can be adopted to enhance other wordnets as well.
%U https://aclanthology.org/2024.icon-1.62/
%P 531-536
Markdown (Informal)
[Shabdocchar: Konkani WordNet Enrichment with Audio Feature](https://aclanthology.org/2024.icon-1.62/) (R. Gawde et al., ICON 2024)
ACL
- Sunayana R. Gawde, Shrikrishna R. Parab, Jayram Ulhas Gawas, Shilpa Neenad Desai, and Jyoti Pawar. 2024. Shabdocchar: Konkani WordNet Enrichment with Audio Feature. In Proceedings of the 21st International Conference on Natural Language Processing (ICON), pages 531–536, AU-KBC Research Centre, Chennai, India. NLP Association of India (NLPAI).