English Alphabet Recognition with Telephone Speech

Part of Advances in Neural Information Processing Systems 4 (NIPS 1991)

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Authors

Mark Fanty, Ronald Cole, Krist Roginski

Abstract

A recognition system is reported which recognizes names spelled over the telephone with brief pauses between letters. The system uses separate neural networks to locate segment boundaries and classify letters. The letter scores are then used to search a database of names to find the best scoring name. The speaker-independent classification rate for spoken let(cid:173) ters is 89%. The system retrieves the correct name, spelled with pauses between letters, 91 % of the time from a database of 50,000 names.