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With the exponential growth in the number of mobile devices, voice enabled local search is emerging as one of the most popular applications. Although the application is essentially an integration of automatic speech recognition (ASR) and text or database search, the potential usefulness of this application has been widely acknowledged. In this paper, we present a data-driven approach to voice query parsing, that segments the input query into several fields that are necessary for high-precisiondoi:10.1109/icassp.2009.4960699 dblp:conf/icassp/FengB09 fatcat:bhwnrtndwzb6hkueodnfboejlq