I've reviewed every PDF editor out there - then I had ChatGPT build me a better one

The smartest way to use AI may not be letting it interact with your files, but asking it to write software that handles them ...
Scientific Research Publishing

Cybersecurity and Forensic Audio Analysis: Deepfake Detection Based on MFCC, Audio-Text Disconsistency, and Prosodic Features ()

1 Department of Computer and Instructional Technologies Education, Gazi Faculty of Education, Gazi University, Ankara, Türkiye. 2 Department of Forensic Informatics, Institute of Informatics, Gazi ...
Frontiers

Noninvasive prescreening of pediatric adenoid hypertrophy using quantified MFCC statistics and clinical features: development and external validation

In a dual-center cross-sectional study (N = 202), Center 1 (Capital Center for Children’s Health, Capital Medical University, n = 161) served as the development cohort and Center 2 (College of ...
IEEE

Deep Learning Driven Automated System for Speech Emotion Recognition

Abstract: Speech Emotion Recognition (SER) plays a significant role in many applications such as psychology and speech therapy, customer service, as well as human-computer interaction. We serve this ...
IEEE

Classroom Acoustic Event Detection System

Abstract: Classroom environments often struggle with maintaining optimal acoustic conditions for effective learning. Traditional monitoring methods are manual, time-consuming, and unreliable. This ...
GitHub

HTK features in Python

HTK is a respected toolkit used mainly by the speech community to perform research in speech recognition. Although quite old, many newer systems emulate the same feature extraction pipeline as used in ...
scienceopen.com

Responsible Artificial Intelligence for Mental Health Disorders: Current Applications and Future Challenges

Mental health disorders (MHDs) have significant medical and financial impacts on patients and society. Despite the potential opportunities for artificial intelligence (AI) in the mental health field, ...
Frontiers

Enhanced classification and severity prediction of major depressive disorder using acoustic features and machine learning

Previous studies have classified major depression and healthy control groups based on vocal acoustic features, but the classification accuracy needs to be improved. Therefore, this study utilized deep ...