Practical enhanced Boolean retrieval: experiences with SMART and SIRE systems
Information Processing and Management: an International Journal - The Potential for Improvments in Commerical Document Retrieval Systems
Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
A system for retrieving speech documents
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Trends in Speech Recognition
Information Retrieval
Metadata for integrating speech documents in a text retrieval system
ACM SIGMOD Record
Information Retrieval can Cope with Many Errors
Information Retrieval
Sub-Word Indexing and Blind Relevance Feedback for English, Bengali, Hindi, and Marathi IR
ACM Transactions on Asian Language Information Processing (TALIP)
Spoken Content Retrieval: A Survey of Techniques and Technologies
Foundations and Trends in Information Retrieval
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We show how the recognition performance of a speech recognition component in a speech retrieval system affects the retrieval effectiveness. A speech retrieval system facilitates content-based retrieval of speech documents, i.e. audio recordings containing spoken text. The speech retrieval process receives queries from users and for every query it ranks the speech documents in decreasing order of their probabilities that they are relevant to the query. The speech recognition component is an important part of a speech retrieval system, since it detects the occurrences of indexing features in the documents. Because the recognition of indexing features in continuous speech is error prone, the question arises how much an error prone recognition of indexing features affects the retrieval effectiveness. As an answer to this question and main contribution of this paper we simulated the recognition of indexing features in speech documents on standard information retrieval test collections and show the resulting retrieval accuracies.