Results 21 to 30 of about 7,207 (210)
Automatic Speaker Recognition with Multi-Resolution Gaussian Mixture Models (MR-GMM) [PDF]
The International Journal of Forensic Computer Science, 2009 Gaussian Mixture Models (GMMs) are the most widely used technique for voice modeling in automatic speaker recognition systems. In this paper, we introduce a variation of the traditional GMM approach that uses models with variable complexity (resolution).
D’Almeida, Frederico Quadros +3 more
openaire +2 more sources
Chemical Engineering Transactions, 2016 Gaussian mixture model (GMM) and Gaussian mixture regression (GMR) can be used to detect adulteration in extra virgin olive oil. The estimate of the GMM parameters is commonly obtained from the expectation- maximization (EM) algorithm.
X. Xie, Y. Gao, W.M. Shi, Q. Shen
doaj +1 more source
Orthogonal Wavelet Transform-Based Gaussian Mixture Model for Bearing Fault Diagnosis
Discrete Dynamics in Nature and Society, 2023 The Gaussian mixture model (GMM) is an unsupervised clustering machine learning algorithm. This procedure involves the combination of multiple probability distributions to describe different sample spaces.
Weipeng Li, Yan Cao, Lijuan Li, Siyu Hou
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Jixie qiangdu, 2023 In order to study the frequency domain calculation method of non-Gaussian excitation, Gaussian mixture model（GMM） is introduced. The measured non-Gaussian excitation is transformed into probabilistic power spectrum（PPSD） through GMM model, so that the ...
XU Yang +3 more
doaj
POLARIMETRIC SAR DATA GMM CLASSIFICATION BASED ON IMPROVED FREEMAN INCOHERENT DECOMPOSITION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 Due to the increasing volume of available SAR Data, powerful classification processings are needed to interpret the images. GMM (Gaussian Mixture Model) is widely used to model distributions.
S. Rouabah, M. Ouarzeddine, B. Azmedroub
doaj +1 more source
CGMVAE: Coupling GMM Prior and GMM Estimator for Unsupervised Clustering and Disentanglement
IEEE Access, 2021 Impressive progress has been recently witnessed on deep unsupervised clustering and feature disentanglement. In this paper, we propose a novel method on top of one recent architecture with a novel explanation of Gaussian mixture model (GMM) membership ...
Chunzhi Gu +3 more
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Recognition of Aircraft Engine Sound Based on GMM-UBM Model
MATEC Web of Conferences, 2017 Gaussian mixture model-universal background model (GMM-UBM) is a commonly-used speaker recognition technology, and which has achieved good effect for detection speaker’s sound.
Yuan Shuai, Sun Chengli, Yang Haoge
doaj +1 more source
Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
Speaker Ｒecognition under Limited Data
Journal of Harbin University of Science and Technology, 2017 Speaker recognition has attracted broad and deep research in the past few decades，and manymethods have been proposed. At present，the popular methods such as the Gaussian mixture model-Universal background model( GMM-UBM) and Gaussian mixture model ...
GAI Chao-xu +2 more
doaj +1 more source
Advanced Functional Materials, EarlyView.In MOCVD MoS2 memristors, a current compliance‐regulated Ag filament mechanism is revealed. The filament ruptures spontaneously during volatile switching, while subsequent growth proceeds vertically through the MoS2 layers and then laterally along the van der Waals gaps during nonvolatile switching.
Yuan Fa +19 more
wiley +1 more source