Gaussian mixture speaker models
Speaker identification using distributed vector quantization and Gaussian mixture models
... training Gaussian mixture speaker models as a replacement for Expectation Maximization (EM) algorithm to reduce computational ...the speaker data become too large, it faces the time ...
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Speaker Recognition by Combining Gaussian Mixture Model (GMM) Spectral Representation and Phase Information
... extraction, speaker modeling and speaker testing ...extracting speaker-specific features from the speech signal at reduced data ...generate speaker models. The speaker ...
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A Model Selection Based Self Splitting Gaussian Mixture Learning with Application to Speaker Identification
... self-splitting Gaussian mix- ture learning (SGML) algorithm that starts with a single component and successively splits the selected component into two new components until the most appropriate com- ponent number ...
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TEXT INDEPENDENT SPEAKER IDENTIFICATION WITH PRINCIPAL COMPONENT ANALYSIS
... III. SPEAKER IDENTIFICATION MODEL WITH GENERALIZED GAUSSIAN DISTRIBUTION In this section we describe the speaker identification ...independent speaker identification system with Generalized ...
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Text Independent Automatic Speaker Recognition System Using Mel Frequency Cepstrum Coefficient and Gaussian Mixture Models
... In last decades, an increasing interest in security systems has arisen. These systems are very useful since they allow managing security in a very efficient way, reducing the need of human resources. Most of them ...
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A SPEAKER RECOGNITION SYSTEM USING GAUSSIAN MIXTURE MODEL
... samples. Speaker recognition process is delicate to sound because it can strike the voice signal feature extraction ...correct speaker recognition results. This speaker recognition system is built ...
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(SIMT) model is presented. CUDA
... in Speaker Verification (SV) systems. Training the background models from large speech data requires a significant amount of memory and computational ...of speaker verification system based on ...
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EMOTION RECOGNITION FROM SPEECH WITH GAUSSIAN MIXTURE MODELS AND VIA BOOSTED GMM
... There is a lot of work on emotional intelligence, and there are also separate work on extracting other information like age, gender etc. But it has been proved that the voice features keep on changing by age. Similarly ...
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Analysis of a Modern Voice Morphing Approach using Gaussian Mixture Models for Laryngectomees
... A parallel database is sought wherein the source and the target speakers record a matching set of utterances. We narrowed down on the CMU ARCTIC databases [17], constructed at the Language Technologies Institute at ...
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Enhanced load profiling for residential network customers
... Abstract— Anticipating load characteristics on low voltage circuits is an area of increased concern for Distribution Network Operators with uncertainty stemming primarily from the validity of domestic load profiles. ...
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Clustering Sentence-Level Text via a Novel Nebulous Relational Clustering Algorithm
... the mixture model approach, in which a density is modeled as a linear combination of C component densities in the form , where are called mixing coefficients, and represent the prior probability of data point x ...
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A Review on Text-Independent Speaker Verification Techniques in Realistic World
... for speaker verification like GMM ,SVM and UBM were ...hybrid speaker verification techniques like GMM/SVM and GMM/UBM were also ...discussed. Speaker can be identifying efficiently using the ...
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Enhanced Expectation–Maximization Clustering through Gaussian Mixture Models
... Abstract: Clustering is the most important task in data mining. For the intelligent clustering is also the part of the machine learning. Various existing systems are introduced for better clustering. In the past decade ...
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On Semi Supervised Learning of Gaussian Mixture Models for Phonetic Classification
... of Gaussian mixture models using an uni- fied objective function taking both labeled and unlabeled data into ...on models of higher complexity in which the su- pervised method performs ...
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Bayesian Learning of Gaussian Mixture Densities for Hidden Markov Models
... Bayesian Learning of Gaussian Mixture Densities for Hidden Markov Models B a y e s i a n L e a r n i n g of G a u s s i a n M i x t u r e D e n s i t i e s for H i d d e n M a r k o v M o d e l s J e[.] ...
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An Overview on Speaker Identification Technologies
... in speaker identification ...for speaker recognition, was studied ...the speaker recognition performance ...for speaker recognition ...as speaker characteristics for speaker ...
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Gaussian Mixture Models for Human Face Recognition under Illumination Variations
... Despite the well-established significance of phase in face identification, modeling the phase poses several difficulties. Perhaps the biggest challenge arises due to the fact that the phase is an angle and it lies ...
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An Improved Moving Object Detection Algorithm Based on Gaussian Mixture Models
... proposed Gaussian mixture model (GMM) [5] used for background modeling which had been found to cope reliably with slow illumination changes, repetitive motions from clutter, and long-term scene ...of ...
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Gaussian-Induced Convolution for Graphs
... successful models to conduct structured and semi- structured data, ranging from text (Defferrard, Bresson, and Vandergheynst 2016), bioinformatics (Yanardag and Vishwanathan 2015; Niepert, Ahmed, and Kutzkov 2016; ...
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Binomial Gaussian mixture filter
... a Gaussian mixture filter, such that components have smaller covariances and cause smaller linearization errors when nonlinear measurements are used for the state ...other Gaussian mixture ...
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