Arizona State University

Mayo Foundation for Medical Education and Research

General Dynamics Decision Systems, Inc.

Visar Berisha

Andreas Spanias

Julie Liss

Xuan Zhong

William Yost

Michael Dorman

Glen Patrick Abousleman

Jayaraman Jayaraman Thiagarajan

Suren Jayasuriya

Huan Song

Ming Tu

Jacob Peplinski

Todd Schwedt

Harish Krishnamoorthi

Damien W Budge

Megan Willi

Alan Wisler

Jianwei Zhang

Speech analysis devices and methods for identifying migraine attacks are provided. Migraine sufferers can experience changes in speech patterns both during a migraine attack and in a pre-attack phase (e.g., a time period before the migraine attack can be recognized by the migraine sufferer). Embodiments identify or predict migraine attacks during the pre-attack phase and/or the attack phase (such as early stages of a migraine attack) by comparing speech features from one or more speech samples provided by a user against baseline data. The speech features are indicative and/or predictive of migraine onset, and can be personalized to a user and/or based on normative data.

Speech analysis devices and methods for identifying migraine attacks

Systems, methods, and apparatuses to restore degraded speech via a modified diffusion model are described. An exemplary system is specially configured to train a diffusion-based vocoder containing an upsampler, based on pairing original speech x and degraded speech mel-spectrum msamples; train a deep convoluted neural network (CNN) upsampler based on a mean absolute error loss to match the estimated original speech {circumflex over (x)}′ outputted by the diffusion-based vocoder by extracting the upsampler, generating a reference conditioner, and generating a weighted altered conditioner c′. The system further optimizes speech quality to invert non-linear transformation and estimate lost data by feeding the degraded mel-spectrum mthrough the CNN upsampler and feeding the degraded mel-spectrum mthrough the diffusion-based vocoder. The system then generates estimated original speech {circumflex over (x)}′ based on the corresponding degraded speech mel-spectrum m. Other related embodiments are described.

Systems, methods, and apparatuses for restoring degraded speech via a modified diffusion model

Various embodiments of a systems and methods for a triplet network having speaker diarization are disclosed.

Systems and methods for a triplet network with attention for speaker diartzation

Systems and methods use patient speech samples as inputs, use subjective multi-point ratings by speech-language pathologists of multiple perceptual dimensions of patient speech samples as further inputs, and extract laboratory-implemented features from the patient speech samples. A predictive software model learns the relationship between speech acoustics and the subjective ratings of such speech obtained from speech-language pathologists, and is configured to apply this information to evaluate new speech samples. Outputs may include objective evaluation of the plurality of perceptual dimensions for new speech samples and/or evaluation of disease onset, disease progression, or disease treatment efficacy for a condition involving dysarthria as a symptom, utilizing the new speech samples.

Speech analysis algorithmic system and method for objective evaluation and/or disease detection

Disclosed herein are speech therapeutic devices and methods. In one aspect, the speech therapeutic device includes audio input circuitry, signal processing circuitry, and stimulus circuitry. In certain embodiments, the audio input circuitry is configured to provide an input signal that is indicative of speech provided by a user and the signal processing circuitry is configured to utilize a reconfigurable rule that includes a condition, receive the input signal, process the input signal using the reconfigurable rule, and provide an alert signal responsive to attainment of the condition. The stimulus circuitry is configured to receive the alert signal and provide a stimulus to the user. The signal processing circuitry is additionally configured to (i) receive the reconfigurable rule from a communication network, and/or (ii) generate a record indicative of the alert signal, store the record in a memory, and send the record to a communication network.

Speech therapeutic devices and methods

A method and apparatus for determining an auditory pattern associated with an audio segment. An average intensity at each of a first plurality of detector locations on an auditory scale based at least in part on a first plurality of frequency components that describe a signal is determined. A plurality of tonal bands in the audio segment, wherein each tonal band comprises a particular range of detector locations of the first plurality of detector locations is determined. Corresponding strongest frequency components in the tonal bands are determined. A plurality of non-tonal bands is determined, and each non-tonal band is subdivided into multiple sub-bands. Corresponding combined frequency components that are representative of a combined sum of intensities of the first plurality of frequency components that is in a corresponding sub-band are determined. An auditory based on the corresponding strongest frequency components and the corresponding combined frequency components is determined.

Method and system for determining an auditory pattern of an audio segment

A frame is received that has the wideband audio signal. The low band audio signal is encoded to generate an encoded low band signal. The high band signal is analyzed to determine whether the high band signal is perceptually relevant to the low band signal. If the high band signal is not perceptually relevant to the low band signal, the low band signal is encoded and provided in a frame to the decoder without including parameters corresponding to characteristics of the high band signal. If the high band signal is perceptually relevant, the high band signal is encoded to generate an encoded high band signal. The resultant frame that is sent to the decoder will include a combination of the encoded low band signal and the encoded high band signal.

Split-band speech compression based on loudness estimation

In a wireless communication system () configured for default communication of subsectional signals of a first transmit signal () over multiple wireless channels (), a signal selector () and method () detect an intent to convey a voice signal () over one of the wireless channels () from a handset (). The signal selector () and method () prevent communication of one of the subsectional signals (A) over the wireless channel () for a predetermined interval, and enable a transmission attempt of the voice signal (). When a complete dialed digits sequence is detected within the time interval, the handset () is enabled to utilize the wireless channel. However, when a transmission attempt of the voice signal () is unsuccessful or when transmission of the voice signal () terminates, the signal selector () and method () restore default communication of subsectional signals of the first transmit signal ().

Growing community of inventors

Tempe, AZ, United States of America

Visar Berisha