Structural Bayesian Linear Regression for Hidden Markov Models

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Structural Bayesian Linear Regression for Hidden Markov Models

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 regression parameters are usually shared among sets of Gaussians in HMMs where the Gaussian clusters are represented by a tree. This paper realizes a fully Bayesian treatment of linear regression for HMMs considering this regre...

متن کامل

Linear transformation of Hidden Markov Models based on linear regression

This paper treats a linear transformation of word templates in a word recognition system. The object of the transformation, called LMR-transform, is to adapt the recogniser to a new acoustical environment. The transform is derived by linear regression on pairs of word utterances from two different acoustical environments. The use of the transform has been evaluated for recognition accuracy, spe...

متن کامل

Identification of Gait Events combining Bayesian Hidden Markov Models and Linear Regression

The Hidden Markov Model is a probabilistic timeseries model that has recently found application in human motion analysis. HMMs are usually fit directly to time-series data obtained from motion capture systems, using Gaussian observation models and the Expectation Maximization algorithm. The boundaries of the segmentation induced by the HMM are somewhat arbitrary, because the motion capture data...

متن کامل

Structural Bayesian Predictive Adaptation of Hidden Markov Models

Typical transformation-based model adaptation techniques (e.g. MLLR) in speech recognition systems rely on deriving point estimates of some fixed but unknown parameters (e.g. transformation matrices). These techniques face shortcomings in terms of accuracy and flexibility of modeling the mismatch, accuracy in estimating the parameters, and in efficiency of data usage. In this paper we present a...

متن کامل

Variational Bayesian Analysis for Hidden Markov Models

The variational approach to Bayesian inference enables simultaneous estimation of model parameters and model complexity. An interesting feature of this approach is that it appears also to lead to an automatic choice of model complexity. Empirical results from the analysis of hidden Markov models with Gaussian observation densities illustrate this. If the variational algorithm is initialised wit...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Journal of Signal Processing Systems

سال: 2013

ISSN: 1939-8018,1939-8115

DOI: 10.1007/s11265-013-0785-8