A neutral network for isolated-word recognition
Garry Evan Gold · 2003
Algorithms that are implementable by artificial neural networks show promise of augmenting the field of automatic speech recognition. A specific approach to the problem of isolated-word recognition was initiated by Tank and Hopfield. These ideas were applied to a concatenated systems consisting of a vector quantizer, a time concentrator with vector sequences as input and allophones as output and a final stage with allophone sequence as input and isolated words as output. Improvements in the system are discussed; included are the addition of data-dependent 'phenomenological' rules that yield improved results for a single-speaker 35-word vocabulary isolated-word recognition task.>