Evaluating intelligent interfaces for post-editing automatic transcriptions of online video lectures

Video lectures are fast becoming an everyday educational resource in higher education. They are being incorporated into existing university curricula around the world, while also emerging as a key component of the open education movement. In 2007, the Universitat Politècnica de València (UPV) implemented its poliMedia lecture capture system for the creation and publication of quality educational video content and now has a collection of over 10,000 video objects. In 2011, it embarked on the EU-subsidised transLectures project to add automatic subtitles to these videos in both Spanish and other languages. By doing so, it allows access to their educational content by non-native speakers and the deaf and hard-of-hearing, as well as enabling advanced repository management functions. In this paper, following a short introduction to poliMedia, transLectures and Docència en Xarxa (Teaching Online), the UPV s action plan to boost the use of digital resources at the university, we will discuss the three-stage evaluation process carried out with the collaboration of UPV lecturers to find the best interaction protocol for the task of post-editing automatic subtitles.Valor Miró, JD.; Spencer, RN.; Pérez González De Martos, AM.; Garcés Díaz-Munío, GV.; Turró Ribalta, C.; Civera Saiz, J.; Juan Císcar, A. (2014). Evaluating intelligent interfaces for post-editing automatic transcriptions of online video lectures. Open Learning: The Journal of Open and Distance Learning. 29(1):72-85. doi:10.1080/02680513.2014.909722S7285291Fujii, A., Itou, K., & Ishikawa, T. (2006). LODEM: A system for on-demand video lectures. Speech Communication, 48(5), 516-531. doi:10.1016/j.specom.2005.08.006Gilbert, M., Knight, K., & Young, S. (2008). Spoken Language Technology [From the Guest Editors]. IEEE Signal Processing Magazine, 25(3), 15-16. doi:10.1109/msp.2008.918412Leggetter, C. J., & Woodland, P. C. (1995). Maximum likelihood linear regression for speaker adaptation of continuous density hidden Markov models. Computer Speech & Language, 9(2), 171-185. doi:10.1006/csla.1995.0010Proceedings of the 9th ACM SIGCHI New Zealand Chapter’s International Conference on Human-Computer Interaction Design Centered HCI - CHINZ ’08. (2008). doi:10.1145/1496976Martinez-Villaronga, A., del Agua, M. A., Andres-Ferrer, J., & Juan, A. (2013). Language model adaptation for video lectures transcription. 2013 IEEE International Conference on Acoustics, Speech and Signal Processing. doi:10.1109/icassp.2013.6639314Munteanu, C., Baecker, R., & Penn, G. (2008). Collaborative editing for improved usefulness and usability of transcript-enhanced webcasts. Proceeding of the twenty-sixth annual CHI conference on Human factors in computing systems - CHI ’08. doi:10.1145/1357054.1357117Repp, S., Gross, A., & Meinel, C. (2008). Browsing within Lecture Videos Based on the Chain Index of Speech Transcription. IEEE Transactions on Learning Technologies, 1(3), 145-156. doi:10.1109/tlt.2008.22Proceedings of the 2012 ACM international conference on Intelligent User Interfaces - IUI ’12. (2012). doi:10.1145/2166966Serrano, N., Giménez, A., Civera, J., Sanchis, A., & Juan, A. (2013). Interactive handwriting recognition with limited user effort. International Journal on Document Analysis and Recognition (IJDAR), 17(1), 47-59. doi:10.1007/s10032-013-0204-5Torre Toledano, D., Ortega Giménez, A., Teixeira, A., González Rodríguez, J., Hernández Gómez, L., San Segundo Hernández, R., & Ramos Castro, D. (Eds.). (2012). Advances in Speech and Language Technologies for Iberian Languages. Communications in Computer and Information Science. doi:10.1007/978-3-642-35292-8Wald, M. (2006). Creating accessible educational multimedia through editing automatic speech recognition captioning in real time. Interactive Technology and Smart Education, 3(2), 131-141. doi:10.1108/1741565068000005