Third International Conference on Spoken Language Processing (ICSLP 94)
This paper presents a new method for connected-word recognition with confusable vocabularies, such as connected letters. The recognition process is performed in two steps. First, a second-order HMM provides N-best word strings. Then, the strings of confusable letters are discriminated by a procedure based on acoustic knowledge and artificial neural networks (ANN). This method has been tested on an American-English database containing spelled names collected through the telephone network. The results obtained with the first HMM pass and the improvements made with the ANN are presented and discussed. When a 3,300 name dictionary and a retrieval procedure based on a DTW alignment algorithm were used, 96% recognition accuracv was obtained.
Bibliographic reference. Mari, Jean-Frangois / Fohr, Dominique / Anglade, Yolande / Junqua, Jean-Claude (1994): "Hidden Markov models and selectively trained neural networks for connected confusable word recognition", In ICSLP-1994, 1519-1522.