Support System for Lecture Captioning Using Keyword Detection by Automatic Speech Recognition

We propose a support system for lecture captioning. The system can detect the keywords of a lecture and present them to captionists. The captionists can understand what an instructor said even when they cannot understand the keywords, and can input keywords rapidly by pressing the corresponding function key. The system detects the keywords by automatic speech recognition (ASR). To improve the detection rate of keywords, we adapt the language model of ASR using web documents. We collect 2,700 web documents, which include 1.2 million words and 5,800 sentences. We conducted an experiment to detect keywords of a real lecture and showed that the system can achieve higher F-measure of 0.957 than that of a base language model (0.871).