An N-best strategy, dynamic grammars and selectively trained neural networks for real-time recognition of continuously spelled names over the telephone

We introduce SmarTspelL, a new speaker-independent algorithm to recognize continuously spelled names over the telephone. Our method is based on an N-best multi-pass recognition strategy applying costly constraints when the number of possible candidates is low. This strategy outperforms an HMM recognizer using a grammar containing all the possible names. It is also more suitable to real-time implementation. For a 3388 name dictionary, a 95.3% name recognition rate is obtained. A real-time prototype has been implemented on a workstation. We also present comparisons of different feature sets for speech representation, and two speech recognition approaches based on first- and second-order HMMs