Results 51 to 60 of about 3,790,103 (166)
Acoustic lung signals analysis based on Mel frequency cepstral coefficients and self-organizing maps
Revista Facultad de Ingeniería, 2016 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
Integrative Zoology, EarlyView.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
Mel-cepstral Methods For Image Feature Extraction [PDF]
, 2010 A feature extraction method based on two-dimensional (2D) mel-cepstrum is introduced. The concept of one-dimensional (1D) mel-cepstrum which is widely used in speech recognition is extended to 2D in this article.
Çakır, Serdar +4 more
core +1 more source
Bi‐Model Deep Learning Architectures: A Systematic Review of Fusion Strategies and Design Taxonomies
Concurrency and Computation: Practice and Experience, Volume 38, Issue 21, November 2026.ABSTRACT Bi‐model deep learning, the coordinated use of two complementary models or modalities, has emerged as a powerful paradigm for improving predictive accuracy and robustness in complex real‐world applications. However, existing research remains scattered across domain‐specific studies, with no unified account of the architectural patterns, fusion
Jasmin Z. K. Chu +3 more
wiley +1 more source
Polarization Engineering in Vinylene‐Linked COFs Toward Efficient Neuromorphic Computing
Advanced Science, Volume 13, Issue 56, 9 October 2026.A vinyl‐linked covalent organic framework (COF‐DIBPY) was synthesized on a conductive substrate for memristor applications. Redox reactions and bromide migration enable low‐voltage (0.5V) conductance switching with high analog on/off ratio (15.7). The device was further integrated into a speech emotion recognition system for acoustic simulation and ...
Hao Wang +5 more
wiley +1 more source
Доклады Белорусского государственного университета информатики и радиоэлектроникиThe problem of recognizing emotions in a speech signal using mel-frequency cepstral coefficients using a classifier based on the support vector machine has been studied. The RAVDESS data set was used in the experiments.
D. V. Krasnoproshin, M. I. Vashkevich
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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
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The Capacity Of Mel Frequency Cepstral Coefficients For Speech Recognition
, 2017 Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output.
Al-Anzi, Fawaz S., Dia AbuZeina
openaire +2 more sources
Ion‐Gating Reservoir Computing for Preprocessing‐Free Speech Recognition from Throat Vibrations
Advanced Electronic Materials, Volume 12, Issue 19, 12 October 2026.This work presents a throat‐mounted mechanoelectric sensor integrated with an ion‐gel/graphene reservoir device for on‐device speech recognition. The system converts raw biomechanical vibrations into rich nonlinear current dynamics, enabling efficient classification through a simple linear readout. The approach highlights a compact and tunable physical‐
Daiki Nishioka +5 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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