  Speech intelligibility assessment plays an important role in the therapy of
patients suffering from pathological speech disorders. Automatic and objective
measures are desirable to assist therapists in their traditionally subjective
and labor-intensive assessments. In this work, we investigate a novel approach
for obtaining such a measure using the divergence in disentangled latent speech
representations of a parallel utterance pair, obtained from a healthy reference
and a pathological speaker. Experiments on an English database of Cerebral
Palsy patients, using all available utterances per speaker, show high and
significant correlation values (R = -0.9) with subjective intelligibility
measures, while having only minimal deviation (+-0.01) across four different
reference speaker pairs. We also demonstrate the robustness of the proposed
method (R = -0.89 deviating +-0.02 over 1000 iterations) by considering a
significantly smaller amount of utterances per speaker. Our results are among
the first to show that disentangled speech representations can be used for
automatic pathological speech intelligibility assessment, resulting in a
reference speaker pair invariant method, applicable in scenarios with only few
utterances available.
