Performance Assessment of ChatGPT versus Bard in Detecting Alzheimer's Dementia.

Large language models (LLMs) find increasing applications in many fields. Here, three LLM chatbots (ChatGPT-3.5, ChatGPT-4, and Bard) are assessed in their current form, as publicly available, for their ability to recognize Alzheimer's dementia (AD) and Cognitively Normal (CN) individuals using textual input derived from spontaneous speech recordings.

Acoustic characterization of nanofibers for optimization with porous substrate.

Nanofiber-porous systems comprising a porous substrate overlaid with nanofiber weave offer the potential for higher acoustic absorption than the substrate alone with negligible increase in thickness. The characterization of nanofibers from acoustic measurements is investigated in this work, and a regression model for predicting their acoustic properties from a single physical parameter is proposed to enable the design of nanofiber-porous systems directly from fabrication parameters. Characterization as a resistive screen via Johnson-Champoux-Allard and lumped element models for transfer matrix computations of absorption coefficient for nanofiber-porous systems exhibited good agreement with the measured spectra.

Vocal Tract Resonance Detection at Low Frequencies: Improving Physical and Transducer Configurations.

Broadband excitation introduced at the speaker's lips and the evaluation of its corresponding relative acoustic impedance spectrum allow for fast, accurate and non-invasive estimations of vocal tract resonances during speech and singing. However, due to radiation impedance interactions at the lips at low frequencies, it is challenging to make reliable measurements of resonances lower than 500 Hz due to poor signal to noise ratios, limiting investigations of the first vocal tract resonance using such a method. In this paper, various physical configurations which may optimize the acoustic coupling between transducers and the vocal tract are investigated and the practical arrangement which yields the optimal vocal tract resonance detection sensitivity at low frequencies is identified.

Estimating vocal tract geometry from acoustic impedance using deep neural network.

A data-driven approach using artificial neural networks is proposed to address the classic inverse area function problem, i.e., to determine the vocal tract geometry (modelled as a tube of nonuniform cylindrical cross-sections) from the vocal tract acoustic impedance spectrum.

Development and Validation of a Deep Learning System for Sound-based Prediction of Urinary Flow.

Background: Uroflowmetry remains an important tool for the assessment of patients with lower urinary tract symptoms (LUTS), but accuracy can be limited by within-subject variation of urinary flow rates. Voiding acoustics appear to correlate well with conventional uroflowmetry and show promise as a convenient home-based alternative for the monitoring of urinary flows.

Objective: To evaluate the ability of a sound-based deep learning algorithm (Audioflow) to predict uroflowmetry parameters and identify abnormal urinary flow patterns.

Deep Neural Network-Based Respiratory Pathology Classification Using Cough Sounds.

Intelligent systems are transforming the world, as well as our healthcare system. We propose a deep learning-based cough sound classification model that can distinguish between children with healthy versus pathological coughs such as asthma, upper respiratory tract infection (URTI), and lower respiratory tract infection (LRTI). To train a deep neural network model, we collected a new dataset of cough sounds, labelled with a clinician's diagnosis.

Acoustic Effect of Face Mask Design and Material Choice.

Unlabelled: The widespread adoption of face masks is now a standard public health response to the 2020 pandemic. Although studies have shown that wearing a face mask interferes with speech and intelligibility, relating the acoustic response of the mask to design parameters such as fabric choice, number of layers and mask geometry is not well understood. Using a dummy head mounted with a loudspeaker at its mouth generating a broadband signal, we report the acoustic response associated with 10 different masks (different material/design) and the effect of material layers; a small number of masks were found to be almost acoustically transparent (minimal losses).

Asthmatic versus healthy child classification based on cough and vocalised /ɑ:/ sounds.

Cough is a common symptom presenting in asthmatic children. In this investigation, an audio-based classification model is presented that can differentiate between healthy and asthmatic children, based on the combination of cough and vocalised /ɑ:/ sounds. A Gaussian mixture model using mel-frequency cepstral coefficients and constant-Q cepstral coefficients was trained.

Perceptual evaluation of measures of spectral variance.

In many applications, it is desirable to achieve a signal that is as close as possible to ideal white noise. One example is in the design of an artificial reverberator, whereby there is a need for its lossless prototype output from an impulse input to be perceptually white as much as possible. The Ljung-Box test, the Drouiche test, and the Wiener Entropy-also called the Spectral Flatness Measure-are three well-known methods for quantifying the similarity of a given signal to ideal white noise.

The effect of nearby timpani strokes on horn playing.

Horn players have observed that timpani strokes can interfere disruptively with their playing, especially when they are seated close to the timpani. Measuring the horn's transfer function in the bell-to-mouthpiece direction reveals that the horn behaves as an acoustic impedance matching device, capable of transmitting waves with pressure gains of at least 20 dB near horn playing resonances. During moderate to loud timpani strokes, the horn transmits an overall impulse gain response of at least 16 dB from the bell to the mouthpiece, while evidence of non-linear bore propagation can be observed for louder strokes.

Do trumpet players tune resonances of the vocal tract?

The acoustic impedance spectrum was measured in the mouths of seven trumpeters while they played normal notes and while they practiced "bending" the pitch below or above the normal value. The peaks in vocal tract impedance usually had magnitudes rather smaller than those of the bore of the trumpet. Over the range measured, none of the trumpeters showed systematic tuning of the resonances of the vocal tract.

Saxophonists tune vocal tract resonances in advanced performance techniques.

The acoustical impedance spectrum was measured in the mouths of saxophonists while they played. During bugling and while playing in the very high or altissimo range, experienced players tune a strong, but relatively broad, peak in the tract impedance to select which peak in the bore impedance will determine the note. Less experienced players are unable to produce resonances with impedance peaks comparable in magnitude to those of the bore and consequently are unable to play these notes.

Experienced saxophonists learn to tune their vocal tracts.

Acousticians have long debated whether and how the resonances of the vocal tract are involved in the playing of clarinet and saxophone. We measured the resonances of saxophonists' vocal tracts directly while they played. Over most of the instrument's range, there is no simple relation between tract resonances and the note played, and the tract resonances varied among players.