A new system for automatic analysis and quality adjustment in audiovisual subtitled‐based contents by means of genetic algorithms. Issue 6 (8th January 2020)

• Record Type: Journal Article
• Authors: Souto‐Rico, Monica; González‐Carrasco, Israel; López‐Cuadrado, José‐Luis; Ruíz‐Mezcua, Belén
• Other Names: Gonzalez‐Pardo Antonio guestEditor.; Tallón‐Ballesteros Antonio J. guestEditor.; Yin Hujun guestEditor.; Cortez Paulo guestEditor.; Bifet Albert guestEditor.
• Is Part Of: Expert systems. Volume 37:Issue 6(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-01-08
• Subjects: automatic subtitle adjustment -- big data -- genetic algorithms -- massive knowledge integration; Expert systems (Computer science); 006.33
• DOI: 10.1111/exsy.12512
• Languages: English
• ISSNs: 0266-4720

Abstract

Abstract: In Spain, the subtitling service on television for the deaf has been improving in quantity since the General Law on Audiovisual Communication was enacted in 2010. This law establishes a series of quality standards that must be followed in the subtitling process. One of the most relevant aspects of subtitle quality is the speed at which they are shown on the screen, due to the fact that a too high speed (less time on screen) will make them difficult to read and the information hard to understand. In order to determine whether the speed at which the subtitles are being shown is adequate, first, it is necessary to process all the information associated with the broadcast of the digital TV channels including data from different sources. In this research, the authors have worked with the data obtained within the time period between July 2012 and December 2017, that is, with more than 950 million records. This article presents a framework for integration and processing of heterogeneous information associated with the subtitling of audiovisual content from different sources. Moreover, the framework will provide an automatic adjustment of subtitles in broadcasting regarding quality indicators by means of a genetic algorithm approach. The results show that the system is able to estimate the best relationship between the time and size of the subtitles and maintaining the quality levels established for this research. These results have been validated by experts and users of this domain.