Feature-based speaker-independent recognition of isolated english letters

FEATURE is a speaker-independent isolated letter recognition system. The system performs a series of feature measurements on an input utterance, then classifies the sound as one of 26 English letters using statistical pattern classification techniques. Performance was evaluated for 10 male and 10 female speakers. For each speaker tested, the system was trained on 4 tokens of each letter provided by the remaining 19 speakers. The average error rate was 10.5%. The system can be used in either a speaker-independent or dynamic adaptation mode. In this latter mode, the user provides feedback when an error is made, and the system changes the statistical parameters that are used during classification. In this way, the system dynamically adapts to the speech patterns of the current user. The use of tuning produced a decrease in the error rate from 10.5% to 6.2%, averaged across the 20 speakers. FEATURE is significant because it is able to perform fine phonetic distinctions (such as between the letters B-D-E, P-T-G, V-Z, M-N, J-K, I-R) in a speaker- independent mode.