Detection of neurological diseases such as Parkinson's disease can be accomplished through analyzing a subject's speech for acoustic measures based on human factor cepstral coefficients (HFCC). Upon receiving a speech sample from a subject, a signal analysis can be performed that includes identifying articulation range and articulation rate using HFCC and delta coefficients. A likelihood of Parkinson's disease, for example, can be determined based upon the identified articulation range and articulation rate of the speech.