Brain-Computer Interfaces (BCI) that could decode thoughts into commands would improve the quality of life of patients who have lost control over voluntary muscles. Imagined speech consists in imagining the pronunciation of words, without moving or emitting sounds. In this study, we introduce a new open access database of electroencephalogram (EEG) signals recorded while 15 subjects imagined the pronunciation of two groups of Spanish words. The first one contained the vowels /a/, /e /, /i/, /o/, /u/; and the second one corresponds to the commands up, down, left, right, backward and forward. Each subject repeated each word 50 times in a random order, meanwhile EEG signals were recorded using a six channel acquisition system and sampled at 1024 Hz. For comparison, some blocks were recorded using the pronounced speech condition, in which audio and EEG signals were acquired simultaneously. The EEG signals were filtered for artifact’s removal between 2 Hz and 40 Hz using a finite impulse response (FIR) pass-band filter. As a preliminary analysis of the EEG data, an offline classification method is presented. Accuracy rate is above chance level for almost all subjects, suggesting that EEG signals possess discriminative information about the imagined word.