In this work, we describe a subword unit approach for information retrieval of items by voice. An algorithm based on the minimum description length (MDL) principle converts an index written in terms of words into an index written in terms of phonetic subword units. A speech recognition engine that uses a language model and pronunciation dictionary built from such an inventory of subword units is completely independent from the information retrieval task. The recognition engine can remain fixed, making this approach ideal for resource constrained systems. In addition, we demonstrate that recall results at higher out of vocabulary (OOV) rates are much superior for the subword unit system. On a music lyrics task at 80% OOV, the subword-based recall is 75.2%, compared to 47.4% for a word system.
Bibliographic reference. Gouvêa, Evandro / Ezzat, Tony (2010): "Vocabulary independent spoken query: a case for subword units", In INTERSPEECH-2010, 1680-1683.