Enhanced Multimedia Content Access and Exploitation Using Semantic Speech Retrieval

Techniques for automatic annotation of spoken content making use of speech recognition technology have long been characterized as holding unrealized promise to provide access to archives inundated with undisclosed multimedia material. This paper provides an overview of techniques and trends in semantic speech retrieval, which is taken to encompass all approaches offering meaning-based access to spoken word collections. We present descriptions, examples and insights for current techniques, including facing real-world heterogenity, aligning parallel resources and exploiting collateral collections. We also discuss ways in which speech recognition technology can be used to create multimedia connections that make new modes of access available to users. We conclude with an overview of the challenges for semantic speech retrieval in the workflow of a real-world archive and perspectives on future tasks in which speech retrieval integrates information related to affect and appeal, dimensions that transcend topic.