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

Patent metadata

Field	Value
Publication number	US-10478111-B2
Application number	US-201515505577-A
Country	US
Kind code	B2
Filing date	Aug 5, 2015
Priority date	Aug 22, 2014
Publication date	Nov 19, 2019
Grant date	Nov 19, 2019

Abstract

A computer-implemented method can include a speech collection module collecting a speech pattern from a patient, a speech feature computation module computing at least one speech feature from the collected speech pattern, a mental health determination module determining a state-of-mind of the patient based at least in part on the at least one computed speech feature, and an output module providing an indication of a diagnosis with regard to a possibility that the patient is suffering from a certain condition such as depression or Post-Traumatic Stress Disorder (PTSD).

First claim

What is claimed is:

1. A computer-implemented method of improving output of a speech-based state-of-mind detection system, the method comprising:
receiving, using the speech-based state-of-mind detection system, a speech pattern collected from a patient;
determining, using the speech-based state-of-mind detection system, at least one feature of the collected speech pattern;
determining, using the speech-based state-of-mind detection system, a presence or absence of a state-of-mind of the patient using a first distribution of a non-lexical speech feature computed over a first time interval in which speech of the patient is collected during a session and a second distribution of the non-lexical speech feature computed over a second time interval in which speech of the patient is collected during the session to indicate a change in the patient from a first state-of-mind to a second state-state-of-mind as a result of the session;
wherein the state-of-mind is defined by a clinical protocol; and
outputting, by the speech-based state-of-mind detection system, the presence or absence of the state-of-mind to the patient, a clinical expert, or both the patient and the clinical expert.

2. The computer-implemented method of claim 1 , wherein the determined state-of-mind indicates a probability that the patient is suffering from at least one of:
depression, suicidal tendencies, Post-Traumatic Stress Disorder (PTSD), a concussion, bipolar disorder, anxiety disorder, mild Traumatic Brain Injury (mTBI), and schizophrenia.

3. The computer-implemented method of claim 1 , further comprising using at least the at least one non-lexical speech feature to build a predictor of the patient's state-of-mind.

4. The computer-implemented method of claim 3 , wherein the using is performed on a remote server.

5. The computer-implemented method of claim 1 , wherein the at least one non-lexical speech feature includes linguistic features and at least one of: prosodic features and spectral features.

6. The computer-implemented method of claim 1 , wherein the at least one non-lexical speech feature corresponds to a pitch of the patient's speech.

7. The computer-implemented method of claim 1 , wherein the at least one non-lexical speech feature corresponds to a harmonicity of the patient's speech.

8. The computer-implemented method of claim 1 , further comprising comparing the determined state-of-mind to an empirical threshold.

9. The computer-implemented method of claim 1 , further comprising: prompting the patient to produce the speech pattern; producing the speech pattern responsive to the prompting; and receiving the produced speech pattern.

10. The computer-implemented method of claim 9 , further comprising analyzing the quality of the received speech pattern.

11. The computer-implemented method of claim 10 , wherein analyzing the quality of the received speech pattern comprises determining whether the analyzed quality of the received speech pattern meets a particular threshold.

12. The computer-implemented method of claim 11 , further comprising causing the prompting, producing, receiving, and analyzing to repeat until the analyzed quality of the received speech pattern meets the particular threshold.

13. The computer-implemented method of claim 9 , wherein prompting the patient to produce the speech pattern comprises presenting to the patient a plurality of open-ended questions.

14. 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.

15. The system of claim 14 , wherein the at least one processor is configured to:
store speech assessment information; and
develop an algorithm configured to be used by the mental health determination module in determining the state-of-mind of the patient.

16. The system of claim 14 , wherein the at least one processor is configured to interact with the mental health determination module over a network.

17. The system of claim 16 , wherein the network is the Internet.

18. The system of claim 14 , wherein the at least one processor is configured to use at least the at least one computed speech feature to build a predictor of the patient's state-of-mind.

19. The system of claim 14 , wherein the at least one processor is a same processor.

20. The system of claim 14 , wherein the determined state-of-mind indicates a probability that the patient is suffering from at least one of: depression, suicidal tendencies, Post-Traumatic Stress Disorder (PTSD), a concussion, bipolar disorder, anxiety disorder, mild Traumatic Brain Injury (mTBI), and schizophrenia.

21. The system of claim 14 , wherein the at least one computed speech feature includes linguistic features and at least one of: prosodic features and spectral features.

22. The system of claim 14 , wherein the at least one speech feature corresponds to a pitch of the patient's speech.

23. The system of claim 14 , wherein the at least one speech feature corresponds to a harmonicity of the patient's speech.

24. The system of claim 14 , wherein the collected speech pattern comprises an answer to a question that was presented to the patient.

25. The system of claim 14 , wherein the collected speech pattern comprises a plurality of answers, each answer corresponding to one of a plurality of questions that were presented to the patient.

26. The system of claim 14 , wherein the at least one processor is configured to check the audio quality of the collected speech pattern.

27. 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 an

Assignees

• Stanford Res Inst Int

Inventors

• Knoth Bruce
• Vergyri Dimitra
• Shriberg Elizabeth
• Mitra Vikramjit
• Mclaren Mitchell
• Kathol Andreas
• Richey Colleen
• Graciarena Martin

Classifications

• G10L17/26

  Recognition of special voice characteristics, e.g. for use in lie detectors; Recognition of animal voices · CPC title

• G10L25/66

  for extracting parameters related to health condition (detecting or measuring for diagnostic purposes A61B5/00) · CPC title

• G10L15/1807

  using prosody or stress · CPC title

• G10L15/1822

  Parsing for meaning understanding · CPC title

• A61B5/165 Primary

  Evaluating the state of mind, e.g. depression, anxiety · CPC title