This paper proposes a phoneme HMM evaluation algorithm that does not require phoneme labeling and that gives a result which is independent of the recognition task. This algorithm is applied to an evaluation of speaker independent HMMs trained by using a speech database uttered by 64 speakers. The algorithm is compared with the conventional evaluation algorithm based on phoneme labels. The results show that the proposed algorithm is highly useful for HMM phoneme model evaluation.