This presentation will deal with a specific case of communication disorder, namely speech and voice disorders. After defining this specific context, we will focus on the assessment of this type of disorder, which is necessary in the clinical field, and on how automatic approaches can overcome the limitations of perceptual assessment, particularly in terms of subjectivity and reproducibility. We will briefly review the classical machine learning approaches used since the 90s and, more recently, the application of deep learning. At this point, we’ll look at the concept of interpretability in deep learning (as we define this concept) and how it can be used to provide useful information to clinicians.