AIMC Topic: Speech

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Mild Cognitive Impairment Detection System Based on Unstructured Spontaneous Speech: Longitudinal Dual-Modal Framework.

JMIR medical informatics
BACKGROUND: In recent years, the incidence of cognitive diseases has also risen with the significant increase in population aging. Among these diseases, Alzheimer disease constitutes a substantial proportion, placing a high-cost burden on health care...

Predicting Ultra-High Risk Outcomes Using Linguistic and Acoustic Measures From High-Risk Social Challenge Recordings: mHealth Longitudinal Cohort Exploratory Study.

JMIR formative research
BACKGROUND: Early detection of individuals at ultra-high risk (UHR) for psychosis is critical for timely intervention and improving clinical outcomes. However, current UHR assessments, which rely heavily on psychometric tools, often suffer from low s...

Developing an AI-driven multimodal approach to visualising resilient team performance: joint attentional engagement with gaze and speech in simulated emergency scenarios.

BMJ open quality
INTRODUCTION: Healthcare team performance directly impacts the quality and safety of medical care. However, measuring the performance of teams is challenging and requires methodologies to investigate different contributing elements. This study propos...

Automated Speech Analysis for Screening and Monitoring Bipolar Depression: Machine Learning Model Development and Interpretation Study.

JMIR medical informatics
BACKGROUND: Depressive episodes in bipolar disorder are frequent, prolonged, and contribute substantially to functional impairment and reduced quality of life. Therefore, early and objective detection of bipolar depression is critical for timely inte...

Improving emotional connection of human and machine using Deep Maxout Networks optimized through Modified Water Cycle optimizer.

Scientific reports
The precise identification and understanding of human emotions by computers is crucial for generating natural interactions between humans and machines. This research presents a novel approach for identifying emotions in speech through the integration...

Speech-based respiratory diagnostics: A study on COVID-19 detection with machine learning.

PloS one
Respiratory sound analysis has emerged as a promising approach for detecting and diagnosing respiratory diseases, including COVID-19. This study investigates using OpenSMILE features for COVID-19 detection using vowel speech sounds /a/, /e/, and /o/ ...

Enhancing Urdu hate speech detection through differential transfer learning and adaptive loss functions.

Scientific reports
Hate speech detection is a challenging task due to complexities such as language ambiguity, limited context, cultural nuances, and situational factors. This challenge is further amplified in low-resource languages, i.e. Urdu. Most research on hate sp...

An Aerosol Jet-Printed Wearable Graphene/Cellulose Nanocrystal Acoustic Sensor for Speech Recognition.

ACS sensors
Wearable acoustic sensors offer a promising solution for effective communication for individuals with speech impairments by calibrating throat vibrations and converting them to synthesized speech. We developed a new type of piezoresistive acoustic se...

Performance of Automatic Speech Analysis in Detecting Depression: Systematic Review and Meta-Analysis.

JMIR mental health
BACKGROUND: Despite the high prevalence and significant burden of depression, underdiagnosis remains a persistent challenge. Automatic speech analysis (ASA) has emerged as a promising method for depression assessment. However, a comprehensive quantit...

CIRE: A Chinese EEG Dataset for decoding speech intention modulated by prosodic emotion.

Scientific data
Neural decoding of speech intention could advance the development and application of brain-computer interface (BCI) technology. Currently, lack of dataset limited the research on decoding the true speech intention, especially the diverse intentions e...