Is spoken Hungarian low-resource? A quantitative survey of Hungarian speech data sets
- Author
- Peter Mihajlik, Katalin Mády, Anna Kohári, Sára Fruzsina, Gábor Kiss, Tekla Etelka Gráczi and A. Seza Doğruöz (UGent)
- Organization
- Abstract
- Even though various speech data sets are available in Hungarian, there is a lack of a general overview about their types and sizes. To fill in this gap, we provide a survey of available data sets in spoken Hungarian in five categories (e.g., monolingual, Hungarian part of multilingual, pathological, child-related and dialectal collections). In total, the estimated size of available data is about 2800 hours (across 7500 speakers) and it represents a rich spoken language diversity. However, the distribution of the data and its alignment to real-life (e.g. speech recognition) tasks is far from optimal indicating the need for additional larger-scale natural language speech data sets. Our survey presents an overview of available data sets for Hungarian explaining their strengths and weaknesses which is useful for researchers working on Hungarian across disciplines. In addition, our survey serves as a starting point towards a unified foundational speech model specific to Hungarian.
- Keywords
- Hungarian, Speech Data, Low-resource Languages, Transcription
Downloads
-
2024.lrec-main.820.pdf
- full text (Published version)
- |
- open access
- |
- |
- 151.39 KB
Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01HZHSJ9D3X4G85QYX6YVWMZTE
- MLA
- Mihajlik, Peter, et al. “Is Spoken Hungarian Low-Resource? A Quantitative Survey of Hungarian Speech Data Sets.” Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), edited by Nicoletta Calzolari et al., ELRA, 2024, pp. 9382–88.
- APA
- Mihajlik, P., Mády, K., Kohári, A., Fruzsina, S., Kiss, G., Gráczi, T. E., & Doğruöz, A. S. (2024). Is spoken Hungarian low-resource? A quantitative survey of Hungarian speech data sets. In N. Calzolari, M.-Y. Kan, V. Hoste, A. Lenci, S. Sakti, & N. Xue (Eds.), Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) (pp. 9382–9388). ELRA.
- Chicago author-date
- Mihajlik, Peter, Katalin Mády, Anna Kohári, Sára Fruzsina, Gábor Kiss, Tekla Etelka Gráczi, and A. Seza Doğruöz. 2024. “Is Spoken Hungarian Low-Resource? A Quantitative Survey of Hungarian Speech Data Sets.” In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), edited by Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, and Nianwen Xue, 9382–88. ELRA.
- Chicago author-date (all authors)
- Mihajlik, Peter, Katalin Mády, Anna Kohári, Sára Fruzsina, Gábor Kiss, Tekla Etelka Gráczi, and A. Seza Doğruöz. 2024. “Is Spoken Hungarian Low-Resource? A Quantitative Survey of Hungarian Speech Data Sets.” In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), ed by. Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, and Nianwen Xue, 9382–9388. ELRA.
- Vancouver
- 1.Mihajlik P, Mády K, Kohári A, Fruzsina S, Kiss G, Gráczi TE, et al. Is spoken Hungarian low-resource? A quantitative survey of Hungarian speech data sets. In: Calzolari N, Kan M-Y, Hoste V, Lenci A, Sakti S, Xue N, editors. Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). ELRA; 2024. p. 9382–8.
- IEEE
- [1]P. Mihajlik et al., “Is spoken Hungarian low-resource? A quantitative survey of Hungarian speech data sets,” in Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), Turin, Italy, 2024, pp. 9382–9388.
@inproceedings{01HZHSJ9D3X4G85QYX6YVWMZTE,
abstract = {{Even though various speech data sets are available in Hungarian, there is a lack of a general overview about their types and sizes. To fill in this gap, we provide a survey of available data sets in spoken Hungarian in five categories (e.g., monolingual, Hungarian part of multilingual, pathological, child-related and dialectal collections). In total, the estimated size of available data is about 2800 hours (across 7500 speakers) and it represents a rich spoken language diversity. However, the distribution of the data and its alignment to real-life (e.g. speech recognition) tasks is far from optimal indicating the need for additional larger-scale natural language speech data sets. Our survey presents an overview of available data sets for Hungarian explaining their strengths and weaknesses which is useful for researchers working on Hungarian across disciplines. In addition, our survey serves as a starting point towards a unified foundational speech model specific to Hungarian.}},
author = {{Mihajlik, Peter and Mády, Katalin and Kohári, Anna and Fruzsina, Sára and Kiss, Gábor and Gráczi, Tekla Etelka and Doğruöz, A. Seza}},
booktitle = {{Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)}},
editor = {{Calzolari, Nicoletta and Kan, Min-Yen and Hoste, Veronique and Lenci, Alessandro and Sakti, Sakriani and Xue, Nianwen}},
isbn = {{9782493814104}},
issn = {{2951-2093}},
keywords = {{Hungarian,Speech Data,Low-resource Languages,Transcription}},
language = {{eng}},
location = {{Turin, Italy}},
pages = {{9382--9388}},
publisher = {{ELRA}},
title = {{Is spoken Hungarian low-resource? A quantitative survey of Hungarian speech data sets}},
url = {{https://aclanthology.org/2024.lrec-main.820}},
year = {{2024}},
}