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The target of this research is decrease or eliminate the training stage, when a new subject uses a braincomputer interface (BCI) based on imagined speech. In the training phase it is necessary to acquire enough information to identify the patterns that allow to distinguish what the subject imagines to pronounce. Then, in imagined speech, like any other evoked potential, the training process is tedious. This article presents experiments that seek to verify if the training information and the available information for a group of subjects can be used for a new person. The proposed method uses selforganized maps to select information in order to generated binary classifiers to identify the words presented in a new EEG subject. The results are encouraged and give the

Hacia un método de transferencia de aprendizaje en señales de EEG de habla imaginada