Variational Bayesian estimation and clustering for speech recognition
In this paper, we propose variational Bayesian estimation and clustering for speech
recognition (VBEC), which is based on the variational Bayesian (VB) approach. VBEC is a …
recognition (VBEC), which is based on the variational Bayesian (VB) approach. VBEC is a …
A parsimonious tour of bayesian model uncertainty
Modern statistical software and machine learning libraries are enabling semi-automated
statistical inference. Within this context, it appears easier and easier to try and fit many …
statistical inference. Within this context, it appears easier and easier to try and fit many …
Simultaneous feature and model selection for continuous hidden Markov models
In this letter, we propose a novel approach of simultaneous feature and model selection for
continuous hidden Markov model (CHMM). In our method, a set of real valued quantities …
continuous hidden Markov model (CHMM). In our method, a set of real valued quantities …
Bayesian adaptive inference and adaptive training
Large-vocabulary speech recognition systems are often built using found data, such as
broadcast news. In contrast to carefully collected data, found data normally contains multiple …
broadcast news. In contrast to carefully collected data, found data normally contains multiple …
[PDF][PDF] Variational Bayesian speaker clustering
F Valente, C Wellekens - ODYSSEY04-The Speaker and Language …, 2004 - Citeseer
In this paper we explore the use of Variational Bayesian (VB) learning in unsupervised
speaker clustering. VB learning is a relatively new learning technique that has the capacity …
speaker clustering. VB learning is a relatively new learning technique that has the capacity …
Joint speech enhancement and speaker identification using approximate Bayesian inference
We present a variational Bayesian algorithm for joint speech enhancement and speaker
identification that makes use of speaker dependent speech priors. Our work is built on the …
identification that makes use of speaker dependent speech priors. Our work is built on the …
[PDF][PDF] Variational Bayesian GMM for speech recognition.
F Valente, C Wellekens - INTERSPEECH, 2003 - isca-archive.org
In this paper, we explore the potentialities of Variational Bayesian (VB) learning for speech
recognition problems. VB methods deal in a more rigorous way with model selection and are …
recognition problems. VB methods deal in a more rigorous way with model selection and are …
A new variational Bayesian algorithm with application to human mobility pattern modeling
A new variational Bayesian (VB) algorithm, split and eliminate VB (SEVB), for modeling data
via a Gaussian mixture model (GMM) is developed. This new algorithm makes use of …
via a Gaussian mixture model (GMM) is developed. This new algorithm makes use of …
Structural Bayesian linear regression for hidden Markov models
Abstract Linear regression for Hidden Markov Model (HMM) parameters is widely used for
the adaptive training of time series pattern analysis especially for speech processing. The …
the adaptive training of time series pattern analysis especially for speech processing. The …
[PDF][PDF] Kernel methods for text-independent speaker verification
C Longworth - 2010 - mi.eng.cam.ac.uk
In recent years, systems based on support vector machines (SVMs) have become standard
for speaker verification (SV) tasks. An important aspect of these systems is the dynamic …
for speaker verification (SV) tasks. An important aspect of these systems is the dynamic …