TED Talk Teaser Generation with Pre-Trained Models

While we have seen significant advances in automatic summarization for text, research on speech summarization is still limited. In this work, we address the challenge of automatically generating teasers for TED talks. In the first step, we create a corpus for automatic summarization of TED and TEDx talks consisting of the talks' recording, their transcripts and their descriptions. The corpus is used to build a speech summarization system for the task. We adapt and combine pre-trained models for automatic speech recognition (ASR) and text summarization using the collected data. This initial work shows that is more important to adapt the summarization model to the ASR transcripts than to adapt the ASR model to the talks.