Speaker-independent name retrieval from spellings using a database of 50000 names

摘要

A system that recognizes names spelled with pauses between letters using high quality speech is described. The system uses neural network classifiers to locate and classify letters, then searches a database of names to find the best match to the letter scores. The directory name retrieval system was evaluated on 1020 names provided by 34 speakers who were not used to train the system. Using a database of 50000 names, 972, or 95.3%, were correctly identified as the first choice. Of the remaining 48 names, all but 10 were in the top three choices. 99% of letters were correctly located, although speakers failed to pause completely about 10% of the time. Classification of individual spoken letters that were correctly located was 93%.