Results 91 to 100 of about 3,633,480 (246)

High Security and Capacity of Image Steganography for Hiding Human Speech Based on Spatial and Cepstral Domains

ARO-The Scientific Journal of Koya University, 2020
A new technique of hiding a speech signal clip inside a digital color image is proposed in this paper to improve steganography security and loading capacity.
Yazen A. Khaleel
doaj   +1 more source

Diagnosis of Parkinson’s Disease based on Wavelet Transform and Mel Frequency Cepstral Coefficients

International Journal of Advanced Computer Science and Applications, 2019
The aim of this study presented in this paper is to determine the choice of the appropriate wavelet analyzer with the method of extraction of MFCC coefficients for an assistance in the diagnosis of Parkinson's disease.
T. B. Drissi, S. Zayrit, B. Nsiri, A. Ammoummou   +3 more
semanticscholar   +1 more source

Machine learning‐assisted vibrational detection and classification of drywood termite infestations

Approaches in Entomology: Methods, Philosophies, and Ethics, Volume 1, Issue 1, August‐December 2026.
Vibratory recordings combined with machine learning accurately detected drywood termite infestations within wood using a fully non‐destructive sensing approach. Models successfully classified termite presence and infestation intensity (empty, low, high density), achieving over 80% accuracy in both internal and external validation.
Lírio Cosme, Raul Narciso C. Guedes, Leonardo M. Turchen   +2 more
wiley   +1 more source

Design Patterns for the Development and Implementation of Bioacoustic Deep Learning Recognizers

Ecology and Evolution, Volume 16, Issue 8, August 2026.
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, Robin Baron, Jesse Whittington   +2 more
wiley   +1 more source

mel-cepstral-distance

<p>For a project description please look at <a href="https://github.com/jasminsternkopf/mel_cepstral_distance">GitHub</a>/<a href="https://pypi.org/project/mel-cepstral-distance">PyPI</a>.</p ...
Taubert, Stefan, Sternkopf, Jasmin
core   +1 more source

Neonatal Pathology Classification From Infant Cry Signals Using a Multi-Branch Graph Neural Network

IEEE Access
Even today, the precise and noninvasive identification of neonatal diseases from infant cry signals remains challenging due to the nonstationary and acoustic heterogeneity of cry patterns.
Layth Herzallah, Mahmoud Hantash, Ahmad Hasasneh, Sari Masri, Chakib Tadj   +4 more
doaj   +1 more source

Speech and Language Markers of Bipolar Disorder: Challenges and Opportunities

Bipolar Disorders, Volume 28, Issue 5, August 2026.
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, Jessica Ahrens, Delphine Raucher‐Chéné, Alban Voppel, Lena Palaniyappan   +4 more
wiley   +1 more source

Comparison of Telephone Recordings and Professional Microphone Recordings for Early Detection of Parkinson's Disease, Using Mel-Frequency Cepstral Coefficients with Gaussian Mixture Models

Interspeech, 2019
Vocal impairments are among the earliest symptoms in Parkinson’s Disease (PD). We adapted a method classically used in speech and speaker recognition, based on Mel-Frequency Cepstral Coefficients (MFCC) extraction and Gaussian Mixture Model (GMM) to ...
Laetitia Jeancolas, G. Mangone, J. Corvol, M. Vidailhet, S. Lehéricy, B. Benkelfat, H. Benali, D. Petrovska-Delacrétaz   +7 more
semanticscholar   +1 more source

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

Advanced Materials, Volume 38, Issue 40, 17 July 2026.
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, Jiaxiang Yi, Hieu Nguyen‐Duc, Tien Nu Hoang Lo, Weili Zhao, Chaoqun Dong, Fabien Sorin, Baris Caglar, Lei Wei, Tung Nguyen‐Dang   +9 more
wiley   +1 more source

Leak Detection in Smart Water Networks Using Tailored Acoustic Features Under Complex Urban Environments

Water Resources Research, Volume 62, Issue 7, July 2026.
Abstract Distributed wireless acoustic sensors, such as accelerometers, in smart water networks are increasingly used to detect leaks before they escalate into pipe breaks. In addition to leak‐induced signals, these sensors also capture acoustic noise generated by pumping and valve operations, pedestrians, traffic, and other environmental sources ...
Wei Zeng, Mark Stephens, Xiang Wang, Ruilin Liu, Martin Lambert, Nhu Do   +5 more
wiley   +1 more source