Monologue Summarization: Extraction of Important Sentences for TV News Commentary Programs

The extraction of important sentences is a key technique for automatic summarization. Whereas most research in this area has targeted written language, we are conducting research on spoken language monologues such as presentations and TV news commentary programs. We collected 50 TV news commentary programs, and experimented with the extraction of important sentences from transcriptions. We used two extraction methods. The first one uses word statistics, and the second one uses the surface features of the sentences. In order to use the latter method, we analyzed the transcriptions and obtained surface features related to the importance of the sentences. The experiments showed that the latter method was better than the former one especially when extracting small sets of sentences. We also mention the ambiguity of judgment by individuals and the contribution of each surface feature to the importance of the sentences.