Speaker-independent name retrieval from spellings using a database of 50000 names
ICASSP '91 Proceedings of the Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference
Subphonetic modeling with Markov states: senone
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
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This paper investigates speaker independent spelling recognition over the telephone using a Markov modeling at two levels : one for the recognition of connected letter sequences and one for the retrieval of the word from a known list. A connected-word speech recognizer must be used in order to deal with natural spellings. And the retrieval procedure has to take into account the insertion and deletion errors as well as the substitution errors. The speech database, recorded from about 180 speakers, contained 6000 sequences (average length of 7 letters) corresponding to the spelling of city names, proper names and random sequences. On the city names test set, before retrieval, the letter error rate was 15.9%. Several retrieval procedures are presented and compared. A Markov modeling approach leads to the best performance with a retrieval error rate of 4.3% for a list of 1000 possible names and 12.4% for a list of 30000 town and city names.