In this paper we present the evaluation of a spoken phonetic corpus designed to train acoustic models for Speech Recognition applications in Basque Language. A complete set of acoustic-phonetic decoding experiments was carried out over the proposed database. Context dependent and independent phoneme units were used in these experiments with two different approaches to acoustic modeling, namely discrete and continuous Hidden Markov Models (HMMs). A complete set of HMMs were trained and tested with the database. Experimental results reveal that the database is large and phonetically rich enough to get great acoustic models to be integrated in Continuous Speech Recognition Systems.