Evaluating AI Assisted Subtitling (bibtex)
	abstract = {Recent advances in artificial intelligence (AI) have led to an increased focus on automating media production. One relevant application area for AI is using speech recognition to create subtitles and closed captions for videos. The AI methods based on machine learning are still not sufficiently reliable in terms of producing perfect or acceptable subtitles. To compensate for this unreliability, AI can be used to build tools that support, rather than replace, human efforts and to create semi-automated workflows. In this paper, we present a prototype for including automated speech recognition for subtitling in an existing production-grade video editing tool. We devised an experiment with 25 participants and tested the efficiency and effectiveness of this tool compared to a fully manual process. The results show that there is a significant increase in both effectiveness and efficiency for novices in subtitling. Furthermore, the participants found the augmented process to be more demanding. We identify some usability issues and design choices that pertain to making augmented subtitling easier. },
	address = {New York, NY, USA},
	author = {Soe, Than Htut and Guribye, Frode and Slavkovik, Marija},
	booktitle = {ACM International Conference on Interactive Media Experiences},
	doi = {10.1145/3452918.3458792},
	isbn = {9781450383899},
	keywords = {Subtitling, Subtitling Tool, Augmented Intelligence, Machine Learning, Assisted Subtitling},
	location = {Virtual Event, USA},
	numpages = {12},
	pages = {96?107},
	publisher = {Association for Computing Machinery},
	series = {IMX '21},
	title = {Evaluating AI Assisted Subtitling},
	url = {https://doi.org/10.1145/3452918.3458792},
	year = {2021},
	bdsk-url-1 = {https://doi.org/10.1145/3452918.3458792}}
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