Abstract
In terms of information accessibility tools for hearing-impaired people, in order to understand meetings, expectations for real-time captioning utilizing speech recognition technology are increasing, from manual handwritten abstracts. However, it is still difficult to provide automatic closed captioning with a practical level of accuracy stably, without regard to various speakers and content. Therefore, we develop a web-based real-time closed captioning system that is easy to use in contact conferences, lectures, forums, etc., through trial and feedback from hearing-impaired people in the company. In this report, we outline this system as well as the results of a simple evaluation conducted inside and outside the company.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Berke, L., Caulfield, C., Huenerfauth, M.: Deaf and hard-of-hearing perspectives on imperfect automatic speech recognition for captioning one-on-one meetings. In: Proceedings of the 19th International ACM SIGACCESS Conference on Computers and Accessibility. ASSETS 2017, New York, NY, USA, pp. 155–164. ACM (2017)
Fujitsu Social Science Laboratory Limited: LiveTalk. http://www.fujitsu.com/jp/group/ssl/products/software/applications/ud/livetalk/index.html
Gaur, Y., Metze, F., Miao, Y., Bigham, J.P.: Using keyword spotting to help humans correct captioning faster. In: 16th Annual Conference of the International Speech Communication Association, INTERSPEECH 2015, pp. 2829–2833 (2015)
Huang, X., Baker, J., Reddy, R.: A historical perspective of speech recognition. Commun. ACM 57(1), 94–103 (2014)
Kafle, S., Huenerfauth, M.: Evaluating the usability of automatically generated captions for people who are deaf or hard of hearing. In: Proceedings of the 19th International ACM SIGACCESS Conference on Computers and Accessibility, ASSETS 2017, New York, NY, USA, pp. 165–174. ACM (2017)
Lasecki, W.S., Miller, C.D., Kushalnagar, R., Bigham, J.P.: Real-time captioning by non-experts with legion scribe. In: Proceedings of the 15th International ACM SIGACCESS Conference on Computers and Accessibility, ASSETS 2013, New York, NY, USA, pp. 56:1–56:2. ACM (2013)
Lasecki, W.S., Miller, C.D., Naim, I., Kushalnagar, R., Sadilek, A., Gildea, D., Bigham, J.P.: Scribe: deep integration of human and machine intelligence to caption speech in real time. Commun. ACM 60(9), 93–100 (2017)
Naim, I., Gildea, D., Lasecki, W., Bigham, J.: Text alignment for real-time crowd captioning. In: North American Chapter of the Association for Computational Linguistics, NAACL 2013, pp. 201–210 (2013)
Nasu, Y., Fujimura, H.: Acoustic event detection and removal using LSTM-CTC for speech recognition. IEICE Tech. Rep. 116(208), 121–126 (2016). (in Japanese)
NICT: SpeechCanvas. http://speechcanvas.nict.go.jp/
Ranchal, R., Taber-Doughty, T., Guo, Y., Bain, K., Martin, H., Robinson, J.P., Duerstock, B.S.: Using speech recognition for real-time captioning and lecture transcription in the classroom. IEEE Trans. Learn. Technol. 6(4), 299–311 (2013)
Shamrock Records Inc: UD Talk. http://udtalk.jp/
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Fume, K., Ashikawa, T., Watanabe, N., Fujimura, H. (2018). Implementation of Automatic Captioning System to Enhance the Accessibility of Meetings. In: Miesenberger, K., Kouroupetroglou, G. (eds) Computers Helping People with Special Needs. ICCHP 2018. Lecture Notes in Computer Science(), vol 10896. Springer, Cham. https://doi.org/10.1007/978-3-319-94277-3_31
Download citation
DOI: https://doi.org/10.1007/978-3-319-94277-3_31
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-94276-6
Online ISBN: 978-3-319-94277-3
eBook Packages: Computer ScienceComputer Science (R0)