Recognition of spelled letter sequences is essential for many real-world applications which involve arbitrary names or addresses. Often the letter sequences carry the sentence's crucial information; therefore, it is important to correctly localize and recognize the spelled string. However, large vocabulary speech recognizers tend to perform poorly on spelled letters, especially if they have to deal with spontaneous speech. The research presented here aims at improving the recognition accuracy of spontaneous speech with embedded spelled-letter sequences. We propose methods to localize spelled-letter segments and reclassify them with a specialized letter recognizer.