The use of semantic and acoustic features for open-domain TED talk summarization

We address the problem of automatic speech summarization on open-domain TED talks. The large vocabulary and diversity of topics from speaker-to-speaker presents significant difficulties. The challenges increase not only how to handle disfluencies and fillers, but also how to extract topic-related meaningful messages within the free talks. Here, we propose to incorporate semantic and acoustic features within the speech summarization technique. In addition, we also propose a new evaluation method for speech summarization by checking semantic similarity between system and human summarization. Experiments results reveal that the proposed methods are effective in spontaneous speech summarization.