Diagnostic techniques based on speech models

A method, comprising:

• obtaining, by a processor, one or more speech models, each of the speech models including (i) one or more acoustic states associated with respective local distance functions such that, given any acoustic feature vector within a domain of the local distance functions, the local distance function of each acoustic state returns a local distance indicating a degree of correspondence between the given acoustic feature vector and the acoustic state, and (ii) provided that the speech model includes multiple acoustic states, allowed transitions between the acoustic states;
• receiving, by the processor, a speech sample produced by a subject while a physiological state of the subject was unknown;
• mapping, by the processor, at least one sample portion of the speech sample to a respective one of the speech models, by:
• computing a plurality of feature vectors that quantify acoustic features of different respective portions of the sample portion, and
• based on the local distance functions and on the allowed transitions included in the speech model, mapping the feature vectors to respective ones of the acoustic states included in the speech model such that a total distance between the feature vectors and the respective ones of the acoustic states is minimized, the total distance being based on respective local distances between the feature vectors and the respective ones of the acoustic states;
• and
• in response to mapping the sample portion to the speech model, communicating, by the processor, an output indicating the physiological state of the subject.

A computer software product comprising a tangible non-transitory computer-readable medium in which program instructions are stored, which instructions, when read by a processor, cause the processor to:

• obtain one or more speech models, each of the speech models including (i) one or more acoustic states associated with respective local distance functions such that, given any acoustic feature vector within a domain of the local distance functions, the local distance function of each acoustic state returns a local distance indicating a degree of correspondence between the given acoustic feature vector and the acoustic state, and (ii) provided that the speech model includes multiple acoustic states, allowed transitions between the acoustic states,
• receive a speech sample produced by a subject while a physiological state of the subject was unknown,
• map at least one sample portion of the speech sample to a respective one of the speech models, by:
• computing a plurality of feature vectors that quantify acoustic features of different respective portions of the sample portion, and
• based on the local distance functions and on the allowed transitions included in the speech model, mapping the feature vectors to respective ones of the acoustic states included in the speech model such that a total distance between the feature vectors and the respective ones of the acoustic states is minimized, the total distance being based on respective local distances between the feature vectors and the respective ones of the acoustic states, and
• in response to mapping the sample portion to the speech model, communicate an output indicating the physiological state of the subject.