Language model adaptation for video lectures transcription

Videolectures are currently being digitised all over the world for its enormous value as reference resource. Many of these lectures are accompanied with slides. The slides offer a great opportunity for improving ASR systems performance. We propose a simple yet powerful extension to the linear interpolation of language models for adapting language models with slide information. Two types of slides are considered, correct slides, and slides automatic extracted from the videos with OCR. Furthermore, we compare both time aligned and unaligned slides. Results report an improvement of up to 3.8 % absolute WER points when using correct slides. Surprisingly, when using automatic slides obtained with poor OCR quality, the ASR system still improves up to 2.2 absolute WER points. The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no 287755 (transLectures). Also supported by the Spanish Government (Plan E, iTrans2 TIN2009-14511). Martínez-Villaronga, A.; Del Agua Teba, MA.; Andrés Ferrer, J.; Juan Císcar, A. (2013). Language model adaptation for video lectures transcription. En Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on. IInstitute of Electrical and Electronics Engineers (IEEE). 8450-8454. https://doi.org/10.1109/ICASSP.2013.6639314