Speech Retrieval Based on Automatic Indexing

We present a system that retrieves audio recordings containing spoken text in response to a given textual query. In particular, we describe indexing methods that automatically describe the content of the recordings. The indexing methods, which are based on phoneme recognition output, take account of speech recognition errors. Additionally, the indexing methods we present are suitable for a language where many word inflections and compounds may occur. To compare different indexing methods, we have evaluated the retrieval effectiveness on a test collection of 1289 documents and 26 queries. The results show that better effectiveness can be achieved when taking into account the characteristics of the underlying speech recognition system.