Results 71 to 80 of about 2,981,759 (215)
The Impact of Speaking Style on Speaker Classification Using Mel-Frequency Cepstral Coefficients [PDF]
زبان پژوهیThis 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
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 +2 more
wiley +1 more source
IEEE AccessWavelet-based front-ends have been extensively utilized in speech processing systems, particularly for recognizing speech and speakers, and have significantly improved their performance.
Ibrahim Missaoui, Zied Lachiri
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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
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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 +2 more
wiley +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 +4 more
wiley +1 more source
<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
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Neonatal Pathology Classification From Infant Cry Signals Using a Multi-Branch Graph Neural Network
IEEE AccessEven 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 +4 more
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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 +9 more
wiley +1 more source
Feature Extracting in the Presence of Environmental Noise, using Subband Adaptive Filtering [PDF]
, 2009 In this work, a new feature extracting method in noisy environments is proposed. The approach is based on subband decomposition of speech signals followed by adaptive filtering in the noisiest subbbands of speech.
Samad, Salina Abdul
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