This paper presents a speaker identification system based on Gaussian Mixture Models (GMM) using the variational. Bayesian method.
May 13, 2021 · This paper presents a text-independent speaker identification system based on Variational Bayesian Gaussian Mixture Model (VBGMM).
Missing: recognition | Show results with:recognition
This interplay between speech enhancement and identification is captured in the iterative variational Bayesian algorithm and is illustrated below. PIC. A ...
In this paper, we propose a Bayesian framework, which constructs shared-state triphone HMMs based on a variational Bayesian approach, and recognizes speech ...
Missing: Speaker | Show results with:Speaker
In this paper we explore the use of Variational Bayesian. (VB) learning in unsupervised speaker clustering. VB learning is a relatively new learning ...
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Joint factor analysis (JFA) has been successfully applied to speaker verification tasks to tackle speaker and session variability. In the sense of Bayesian ...
Abstract: In this paper, we investigate the variational Bayes based I-vector method for speaker diarization of telephone conversations.
This paper presents a text-independent speaker identification system based on Variational Bayesian Gaussian Mixture Model (VBGMM). Four types of features which ...
In this paper, we propose to use variational Bayesian (VB) method to learn the clean speech signal from noisy observation directly.
Missing: Speaker | Show results with:Speaker
In this paper, we propose a Bayesian framework, which constructs shared-state triphone HMMs based on a variational Bayesian approach, and recognizes speech.
Missing: Speaker | Show results with:Speaker