In today’s fast-paced world, users face the challenge of having to consume a lot of content in a short time. This situation is exacerbated by the fact that content is scattered in a range of different languages and locations. This research addresses these challenges using a number of natural language processing techniques: adapting content using automatic text summarization; enhancing content accessibility through machine translation; and altering the delivery modality through speech synthesis. This paper introduces Lean-back Learning (LbL), an information system that delivers automatically generated audio presentations for consumption in a “lean-back” fashion, i.e. hands-busy, eyes-busy situations. These presentations are personalized and are generated using multilingual multi-document text summarization. The paper discusses the system’s components and algorithms, in addition to initial system evaluations.
CITATION STYLE
Lawless, S., Lavin, P., Bayomi, M., Cabral, J. P., & Rami Ghorab, M. (2015). Text summarization and speech synthesis for the automated generation of personalized audio presentations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9103, pp. 307–320). Springer Verlag. https://doi.org/10.1007/978-3-319-19581-0_28
Mendeley helps you to discover research relevant for your work.