Robust automatic intelligibility assessment techniques evaluated on speakers treated for head and neck cancer

► We develop an automatic running speech intelligibility assessment method. ► We derive new text-independent speaker features from a phonological representation. ► We validate the method on a new corpus of patients treated for head and neck cancer. ► We show that it is as reliable as a human listener and able to track a speaker's progress.