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This paper presents a voice recognition experiment for speech understanding. The approach is based on the fact that a voice recognition system can have a big improvement by exploiting the intrinsic redundancy of the spoken natural language, that is by delaying every decision to the highest available information level. Namely any decision taken at phoneme level (acoustic level) carries the loss of a certain amount of information. The linguistic recognition system, we have so far developed, is based on a linguistic model, where decisions are taken only at the full message level. This approach follows the same basic idea of a system now successfully working for Mail Address Optical Recognition (1). Such a system has been successfully improved via EMMA, a spe cial network of associative minicomputers, consisting, for that application, in about 60 processors.