Compiling multi-tiered speech databases into the relational model: experiments with the emu system

The Emu speech database system enables the annotation of speech signals at many levels of detail and provides a mechanism for making links between these levels to produce a hierarchical annotation. Emu provides facilities for searching collections of these annotations according to both sequential and hierarchical criteria. The results of a search can be used to retrieve acoustic and other data stored along with the annotations. One perceived problem with the Emu system is its ability to scale to large databases containing many thousands of utterances. To address this problem we propose a method of translating an Emu database into the relational model, as used by most commercial database systems. Using a Tcl script, the Emu database is converted into a set of tables for the relational database. Queries in the Emu query syntax are translated into SQL and comparisons are made between the query processing time for Emu and the relational database. The results show a marked increase in speed for the relational system on most queries.