This paper describes a set of techniques for improving the performance of automated voice search services intended for mobile users accessing these services over a range of portable devices. Voice search is implemented as a two stage search procedure where string candidates generated by an automatic speech recognition (ASR) system are re-scored in order to identify the best matching entry from a potentially very large application specific database. The work in this paper deals specifically with user utterances that contain spoken letter sequences corresponding to spelled instances of search terms. Methods are investigated for identifying the most likely database entry associated with the decoded utterance. An experimental study is presented describing the characteristics of actual user utterances obtained from a prototype voice search service. The impact of these methods on word error rate is presented.