In addition to health problems, Head and Neck Cancers (HNC) can cause serious speech disorders that can lead to partial or complete loss of speech intel-ligibility in some patients. The clinician's evaluation of the intelligibility level before or after surgical treatment and / or during the rehabilitation phase is an important part of the clinical assessment. Perceptive assessment is the most widely used method in clinical practice to assess the level of intelligibility of a patient despite the limitations associated with it such as subjectivity and moderate reproducibility. In this paper, we propose to overcome these limitations by associating a specific task of speech production based on pseudo-words with an automatic speech processing system, both oriented towards acoustic-phonetic decoding. Compared to human perception, the automatic system reaches very high correlation rates and promising results when applied to a French speech corpus including 41 healthy speakers and 85 patients suffering from HNC.