Class model adaptation for speech summarisation
Pierre Chatain, Edward W. D. Whittaker, Joanna Mrozinski, Sadaoki Furui · 2006
The performance of automatic speech summarisation has been improved in previous experiments by using linguistic model adaptation. We extend such adaptation to the use of class models, whose robustness further improves summarisation performance on a wider variety of objective evaluation metrics such as ROUGE-2 and ROUGE-SU4 used in the text summarisation literature. Summaries made from automatic speech recogniser transcriptions benefit from relative improvements ranging from 6.0% to 22.2% on all investigated metrics.