Abstract: A method includes obtaining one or more speech models, each model including one or more acoustic states and, provided that the model includes multiple acoustic states, allowed transitions therebetween. The method further includes receiving a speech sample produced by a subject while a physiological state of the subject was unknown. The method further includes mapping at least one sample portion of the speech sample to a respective one of the speech models, by computing a plurality of feature vectors quantifying acoustic features of different respective portions of the sample portion, and mapping the feature vectors to respective acoustic states included in the speech model such that a total distance between the feature vectors and the respective acoustic states is minimized. The method further includes, in response to mapping the sample portion to the speech model, communicating an output indicating the physiological state of the subject. Other embodiments are also described.

Abstract: A method includes obtaining a first sequence of reference-sample feature vectors that quantify acoustic features of different respective portions of at least one reference speech sample, which was produced by a subject at a first time while a physiological state of the subject was known, and a second sequence of test-sample feature vectors that quantify the acoustic features of different respective portions of at least one test speech sample, which was produced by the subject at a second time while the physiological state of the subject was unknown. The test-sample feature vectors are mapped to respective ones of the reference-sample feature vectors, under predefined constraints, such that a total distance between the test-sample feature vectors and the respective ones of the reference-sample feature vectors is minimized. In response to the mapping, an output indicating the physiological state of the subject at the second time is generated.

Abstract: Described embodiments include an apparatus that includes a network interface and a processor. The processor is configured to receive, via the network interface, a speech signal that represents speech uttered by a subject, the speech including one or more speech segments, divide the speech signal into multiple frames, such that one or more sequences of the frames represent the speech segments, respectively, compute respective estimated total volumes of air exhaled by the subject while the speech segments were uttered, by, for each of the sequences, computing respective estimated flow rates of air exhaled by the subject during the frames belonging to the sequence and, based on the estimated flow rates, computing a respective one of the estimated total volumes of air, and, in response to the estimated total volumes of air, generate an alert. Other embodiments are also described.

Abstract: At least one speech model, which includes one or more acoustic states exhibited in one or more reference speech samples and defines allowed transitions between the acoustic states, is obtained. At least one test speech sample produced by a subject is received. A plurality of test-sample feature vectors that quantify acoustic features of different respective portions of the test speech sample are computed. The test speech sample is mapped to a minimum-distance sequence of the acoustic states, by mapping the test-sample feature vectors to respective ones of the acoustic states such that a first total distance between the test-sample feature vectors and the respective ones of the acoustic states is minimized. A different, second total distance between the test-sample feature vectors and the respective ones of the acoustic states is computed. Responsively to the second total distance, an output indicating a physiological state of the subject is generated.

Abstract: A method for medical diagnosis includes recording voice signals due to sounds spoken by a patient and recording acoustic signals output, simultaneously with the voice signals, by an acoustic transducer in contact with a thorax of the patient. A transfer function is computed between the recorded voice signals and the recorded acoustic signals or between the recorded acoustic signals and the recorded voice signals. The computed transfer function is evaluated in order to assess a medical condition of the patient.

Abstract: An apparatus includes a communication interface and a processor. The processor is configured to receive, via the communication interface, a plurality of speech samples {um0}, m=1 . . . M, which were uttered by a subject while in a first state with respect to a disease, and using {um0} and at least one reference discriminator, which is not specific to the subject, synthesize a subject-specific discriminator, which is specific to the subject and is configured to generate, in response to one or more test utterances uttered by the subject, an output indicating a likelihood that the subject is in a second state with respect to the disease. Other embodiments are also described.

Abstract: A speech model constructed from reference speech samples, which were produced by a subject at a first time while a physiological state of the subject was known, is obtained. The model includes (i) acoustic states exhibited in the reference speech samples and associated with respective local distance functions, and (ii) allowed transitions between the acoustic states. A test speech sample that was produced by the subject at a second time, while the physiological state of the subject was unknown, is received. Test-sample feature vectors that quantify acoustic features of different respective portions of the test speech sample are computed. Based on the local distance functions and the allowed transitions, the test speech sample is mapped to a minimum-distance sequence of the acoustic states. In response thereto, an output indicating the physiological state of the subject at the second time is generated. Other embodiments are also described.

Abstract: Reference-sample feature vectors that quantify acoustic features of different respective portions of at least one reference speech sample, which was produced by a subject at a first time while a physiological state of the subject was known, are obtained. At least one test speech sample that was produced by the subject at a second time, while the physiological state of the subject was unknown, is received. Test-sample feature vectors that quantify the acoustic features of different respective portions of the test speech sample are computed. The test-sample feature vectors are mapped to respective ones of the reference-sample feature vectors, under predefined constraints, such that a total distance between the test-sample feature vectors and the respective ones of the reference-sample feature vectors is minimized. In response to the mapping, an output indicating the physiological state of the subject at the second time is generated. Other embodiments are also described.

Abstract: Described embodiments include an apparatus that includes a network interface and a processor. The processor is configured to receive, via the network interface, a speech signal that represents speech uttered by a subject, the speech including one or more speech segments, divide the speech signal into multiple frames, such that one or more sequences of the frames represent the speech segments, respectively, compute respective estimated total volumes of air exhaled by the subject while the speech segments were uttered, by, for each of the sequences, computing respective estimated flow rates of air exhaled by the subject during the frames belonging to the sequence and, based on the estimated flow rates, computing a respective one of the estimated total volumes of air, and, in response to the estimated total volumes of air, generate an alert. Other embodiments are also described.

Abstract: Described embodiments include apparatus that includes a network interface (28) and a processor (30). The processor is configured to receive, via the network interface, speech of a subject (22) who suffers from a pulmonary condition related to accumulation of excess fluid, to identify, by analyzing the speech, one or more speech-related parameters of the speech, to assess, in response to the speech-related parameters, a status of the pulmonary condition, and to generate, in response thereto, an output indicative of the status of the pulmonary condition. Other embodiments are also described.

Abstract: Described embodiments include apparatus that includes a network interface (28) and a processor (30). The processor is configured to receive, via the network interface, speech of a subject (22) who suffers from a pulmonary condition related to accumulation of excess fluid, to identify, by analyzing the speech, one or more speech-related parameters of the speech, to assess, in response to the speech-related parameters, a status of the pulmonary condition, and to generate, in response thereto, an output indicative of the status of the pulmonary condition. Other embodiments are also described.