Component-based discriminative classification for hidden Markov models

نویسندگان
چکیده

برای دانلود رایگان 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

Component-based discriminative classification for hidden Markov models

Article history: Received 15 September 2008 Received in revised form 10 March 2009 Accepted 18 March 2009

متن کامل

Hidden Gauss-Markov models for signal classification

Continuous-state hidden Markov models (CS-HMMs) are developed as a tool for signal classification. Analogs of the Baum, Viterbi, and Baum–Welch algorithms are formulated for this class of models. The CS-HMM algorithms are then specialized to hidden Gauss–Markov models (HGMMs) with linear Gaussian state-transition and output densities. A new Gaussian refactorization lemma is used to show that th...

متن کامل

A new look at discriminative training for hidden Markov models

Discriminative training for hidden Markov models (HMMs) has been a central theme in speech recognition research for many years. One most popular technique is minimum classification error (MCE) training, with the objective function closely related to the empirical error rate and with the optimization method based traditionally on gradient descent. In this paper, we provide a new look at the MCE ...

متن کامل

Action Classification using a Discriminative Non-Parametric Hidden Markov Model

We classify human actions occurring in videos, using the skeletal joint positions extracted from a depth image sequence as features. Each action class is represented by a non-parametric Hidden Markov Model (NP-HMM) and the model parameters are learnt in a discriminative way. Specifically, we use a Bayesian framework based on Hierarchical Dirichlet Process (HDP) to automatically infer the cardin...

متن کامل

Timbre-based Drum Pattern Classification using Hidden Markov Models

In order to explore the possibility of a timbre-based rhythm theory, a drum pattern classification system was developed, which is capable of describing the internal structure of a drum groove in a stochastic way. Using an onset detection algorithm, timbral features were extracted at every drum onset of the sample file. Next, a Hidden Markov Model (HMM) was fitted to the data. Local decoding of ...

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: Pattern Recognition

سال: 2009

ISSN: 0031-3203

DOI: 10.1016/j.patcog.2009.03.023