Automatic indexing of key sentences for lecture archives

Automatic extraction of key sentences from lecture audio archives is addressed. The method makes use of the characteristic expressions used in initial utterances of sections, which are defined as discourse markers and derived in an unsupervised manner based on word statistics. The statistics of the discourse markers is then used to define the importance of the sentences. It is also combined with the conventional tf-idf measure for content words. Experimental results confirm the effectiveness of the method using the discourse markers and its combination with the keyword-based method. We also present a statistical method for inserting periods into raw speech transcriptions for improving the readability.