Paper: Summarizing multiple spoken documents: finding evidence from untranscribed audio

ACL ID P09-1062
Title Summarizing multiple spoken documents: finding evidence from untranscribed audio
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

This paper presents a model for summa- rizing multiple untranscribed spoken doc- uments. Without assuming the availabil- ity of transcripts, the model modifies a recently proposed unsupervised algorithm to detect re-occurring acoustic patterns in speech and uses them to estimate similari- ties between utterances, which are in turn used to identify salient utterances and re- move redundancies. This model is of in- terest due to its independence from spo- ken language transcription, an error-prone and resource-intensive process, its abil- ity to integrate multiple sources of infor- mation on the same topic, and its novel use of acoustic patterns that extends pre- vious work on low-level prosodic feature detection. We compare the performance of this model with that achieved using man- ual and...