The impact of voice pathologies caused by physiological alterations of the vocal cords is becoming a very important issue due to vocal abuse and unhealthy habits. Early detection of incipient damage to the cords may help in improving the prognosis, treatment and care of these pathologies. Information derived from the speech signal may help in detecting early stages of pathology, and to prevent them by assisting experts in voice therapy to correct vocal abuse in children and in professionals depending on voice as, for example, speakers, singers or lecturers. The present paper is devoted to detecting the presence of certain pathologies in the voice or speech signal from the cepstral contents of the mucosal wave reconstructed by inverse filtering, using conclusions derived from the behavior of a 2-mass vocal cord model. This can be of application in speech and singing education, and in pathology screening.