Systems for speech-based assessment of a patient's state-of-mind

A system for improving output of an automated speech-based state-of-mind detection process, the system comprising at least one processor configured to:

• receive, using the speech-based state-of-mind detection process, a speech pattern collected from a patient;
• compute, from the collected speech pattern, using the speech-based state-of-mind detection process, at least one non-lexical speech feature that indicates a condition of equipment used to collect the speech pattern or a physical environment in which the speech pattern was collected;
• determine a presence or absence of a state-of-mind of the patient using the at least one computed non-lexical speech feature that indicates a condition of equipment used to collect the speech pattern or a physical environment in which the speech pattern was collected,
• wherein the state-of-mind is defined by a clinical protocol,
• wherein the presence or absence of the state-of-mind is using at least one model that models speech patterns of healthy speakers and models speech patterns of speakers that have been positively diagnosed with the state-of-mind;
• and
• outputting, by the speech-based state-of-mind detection process, an indication of the presence or absence of the state-of-mind to the patient, a clinical expert, or both the patient and the clinical expert.

A computer-implemented method for improving output of a speech-based state-of-mind detection system, the method comprising:

• receiving, by the speech-based state-of-mind detection system, a speech pattern collected from a patient;
• computing, by the speech-based state-of-mind detection system, a plurality of speech features from the collected speech pattern;
• determining, by the speech-based state-of-mind detection system using the plurality of speech features, a presence or absence of a state-of-mind of the patient;
• wherein the state-of-mind is defined by a clinical protocol,
• wherein the presence or absence of the state-of-mind is determined using at least one model that models speech patterns of healthy speakers and models speech patterns of speakers that have been positively diagnosed with the state-of-mind,
• wherein the plurality of speech features comprises at least two of any of the following:
• Damped Oscillator Cepstral Coefficients (DOCCs), Normalized Modulation Cepstral Coefficients (NMCCs), Medium Duration Speech Amplitudes (MMeDuSA), Gammatone Cepstral Coefficients (GCCs), DeepTVs, a syllable duration, a speaking rate, a speech rhythmicity, a tilt feature;
• outputting, by the speech-based state-of-mind detection system, the determined state-of-mind to the patient or a clinical expert or both the patient and the clinical expert.