Results 51 to 60 of about 3,467 (180)
Acoustic lung signals analysis based on Mel frequency cepstral coefficients and self-organizing maps
This study analyzes acoustic lung signals with different abnormalities, using Mel Frequency Cepstral Coefficients (MFCC), Self-Organizing Maps (SOM), and K-means clustering algorithm. SOM models are known as artificial neural networks than can be trained
Álvaro David Orjuela-Cañón +1 more
doaj +1 more source
Mel Frequency Cepstral Coefficients: An Evaluation Of Robustness Of Mp3 Encoded Music.
[TODO] Add abstract here.
Sigurdsson, Sigurdur +2 more
openaire +2 more sources
ABSTRACT Objective To provide a comprehensive review of the current landscape of artificial intelligence (AI) applications in voice disorder, with emphasis on emerging applications, limitations, and future directions for clinical integration. Methods Literature review.
Rachel B. Kutler, Anaïs Rameau
wiley +1 more source
Research on mosquito feeding preferences and the malaria parasites they transmit is essential for understanding the interactions between hosts, vectors, and parasites. In this study, vertebrate hosts were identified in 72 mosquitoes. Most blood meals (58.7%) came from birds, representing 25 species, while 40.0% came from mammals (13 species), and 1.3 ...
Qin Zhang +8 more
wiley +1 more source
The paper describes an approach to design a system for analyzing and classification of a voice signal based on perturbation parameters and cepstral representation.
M. I. Vashkevich +2 more
doaj +1 more source
Multi‐Modal AI Approach in Depression Detection and Treatment: A Systematic Review of Last Decade
Overview of multimodal approaches for depression detection and treatment. ABSTRACT Depression is a common and devastating mental health illness with serious personal and societal consequences. Despite advancing treatment techniques, there are still hurdles in the effective diagnosis and treatment of depression, such as prompt diagnosis, personalized ...
Smith K. Khare +3 more
wiley +1 more source
The Impact of Speaking Style on Speaker Classification Using Mel-Frequency Cepstral Coefficients [PDF]
This research investigates the impact of different speaking styles (read and spontaneous) on speaker identification accuracy. Mel-Frequency Cepstral Coefficients (MFCCs) were employed as input features, and the Random Forest algorithm was used for ...
Homa Asadi
doaj +1 more source
Design Patterns for the Development and Implementation of Bioacoustic Deep Learning Recognizers
This paper presents a set of design patterns for developing and integrating Convolutional Neural Network (CNN) recognizers in bioacoustic monitoring programs. Using a western toad case study, we illustrate solutions to common challenges in model development and workflow integration. These patterns provide a practical framework to improve the efficiency,
Gavin Hurd +2 more
wiley +1 more source
Speech and Language Markers of Bipolar Disorder: Challenges and Opportunities
ABSTRACT Background Clinicians aspire to predict the emergence of Bipolar Disorder (BD) in a timely manner. To accomplish this, markers reflecting mental states that can be gathered non‐invasively and at large scale are needed. Here, we systematically evaluate evidence relating speech‐based markers to mood states in BD.
Farida Zaher +4 more
wiley +1 more source
Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung +9 more
wiley +1 more source

