Abstract
This paper describes a speech recognition based closed captioning system for Estonian language, primarily intended for the hard-of-hearing community. The system automatically identifies Estonian speech segments, converts speech to text using Kaldi-based TDNN-F models, and applies punctuation insertion and inverse text normalization. The word error rate of the system is 8.5% for television news programs and 13.4% for talk shows. The system is used by the Estonian Public Television for captioning live native language broadcasts and by the Estonian Parliament for captioning its live video feeds. Qualitative evaluation with the target audience showed that while the existence of closed captioning is crucial, the most important aspects that need to be improved are the ASR quality and better synchronization of the captions with the audio.- Anthology ID:
- 2023.nodalida-1.49
- Volume:
- Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)
- Month:
- May
- Year:
- 2023
- Address:
- Tórshavn, Faroe Islands
- Editors:
- Tanel Alumäe, Mark Fishel
- Venue:
- NoDaLiDa
- SIG:
- Publisher:
- University of Tartu Library
- Note:
- Pages:
- 492–499
- Language:
- URL:
- https://aclanthology.org/2023.nodalida-1.49
- DOI:
- Cite (ACL):
- Tanel Alumäe, Joonas Kalda, Külliki Bode, and Martin Kaitsa. 2023. Automatic Closed Captioning for Estonian Live Broadcasts. In Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa), pages 492–499, Tórshavn, Faroe Islands. University of Tartu Library.
- Cite (Informal):
- Automatic Closed Captioning for Estonian Live Broadcasts (Alumäe et al., NoDaLiDa 2023)
- PDF:
- https://preview.aclanthology.org/corrections-2024-07/2023.nodalida-1.49.pdf