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Speaker-Independent Digit Recognition Using a Neural Network with Time-Delayed Connections
The capability of a small neural network to perform speaker-independent recognition of spoken digits in connected speech has been investigated. The network uses time delays to organize rapidly changing outputs of symbol detectors over the time scale of a word. The network is data driven and unclocked. To achieve useful accuracy in a speakerindependent setting, many new ideas and procedures were developed. These include improving the feature detectors, self-recognition of word ends, reduction indoi:10.1162/neco.1922.214.171.124 fatcat:sgaelftzqnfifgpf62dbfkjw4e