Automatic summarization of spoken documents (e.g., everyday meetings, broadcast news, lectures, political speeches) provides an efficient way for information access in these data sources. Different summarization approaches have been developed and evaluated for speech data in different domains, such as meetings, broadcast news, and lectures. However, compared to text summarization, speech summarization is not as mature. There are no benchmark tests, the evaluation metrics are not clear, and there are not many annotated data sets available. Because of the recent increasing interest in speech summarization in the community, there is a need to gather researchers in the field to discuss various issues in this task and future research directions. This workshop brings together researchers dedicated to speech summarization in various aspects, helps build a research community for this task, and fosters discussions about open problems, future directions, data collection and sharing, algorithms and results. The topics discussed include the definition of speech summarization, data collection and annotation, data sharing, evaluation metrics, possible shared tasks, domain effect, summarization approaches, similarity and differences between text and speech summarization, and modality beyond speech in human communication. The discussions from this meeting will be disseminated using a dedicated website. This meeting will greatly help move forward the research in speech summarization. Students participating in this meeting will benefit from the discussions and be able to use them in their future research.
