Impaired speech intelligibility in motor speech disorders arising due to neurological diseases negatively affects the communication ability and quality of life of patients. Reliable and cost-effective measures to automatically assess speech intelligibility are necessary for the management of such disorders. In this paper, we propose to automatically assess the intelligibility of pathological speech based on short-time objective intelligibility measures typically used in speech enhancement, which however require a reference signal that is time-aligned to the test signal. We propose a method to create an utterance-dependent reference signal of intelligible speech from multiple healthy speakers. In order to assess intelligibility, the pathological speech signal is aligned to the created reference signal using dynamic time warping and the divergence between the two signals is quantified using either the short-time or the spectral correlation. Experiments on databases of English and French patients suffering from Cerebral Palsy and Amyotrophic Lateral Sclerosis show that the proposed intelligibility measures can obtain a high correlation with subjective intelligibility ratings, outperforming several state-of-the-art pathological speech intelligibility measures.