Cross-language speech retrieval: establishing a baseline performance
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
DL '97 Proceedings of the second ACM international conference on Digital libraries
New techniques for open-vocabulary spoken document retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Advances in phonetic word spotting
Proceedings of the tenth international conference on Information and knowledge management
Multilingual information access
Lectures on information retrieval
New Approaches to Spoken Document Retrieval
Information Retrieval
Multilingual Information Access
ESSIR '00 Proceedings of the Third European Summer-School on Lectures on Information Retrieval-Revised Lectures
Vocabulary independent spoken term detection
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Word and sub-word indexing approaches for reducing the effects of OOV queries on spoken audio
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Combining LVCSR and vocabulary-independent ranked utterance retrieval for robust speech search
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Direct posterior confidence for out-of-vocabulary spoken term detection
ACM Transactions on Information Systems (TOIS)
Spoken Content Retrieval: A Survey of Techniques and Technologies
Foundations and Trends in Information Retrieval
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The "topic classification" systems described in the speech literature typically partition a collection of spoken messages into a small number of pre-defined topics. As such, they are only useful if the set of message topics does not vary over time. However, the techniques of textual information retrieval (IR) have long allowed for retrieval by arbitrary subject from a document collection. This paper describes experiments in unrestricted retrieval from a collection of radio news broadcasts. A hybrid message indexing strategy, with conventional word recognition and a fast lattice-based wordspotter, allows for the retrieval of news reports concerning any subject. The results show that retrieval can be carried out extremely quickly and that high accuracy is possible, even with recognition output errors.