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 in

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... network size, and dividing speakers into natural classes. Quantitative experiments based on Texas Instruments (TI) digit data bases are described.