GMTK: The Graphical Models Toolkit
Jeffrey A. Bilmes, Richard Rogers

Citation
Jeffrey A. Bilmes, Richard Rogers. "GMTK: The Graphical Models Toolkit". University of Washington, 10, February, 2015.

Abstract
The Graphical Models Toolkit (GMTK) is an open source, publicly available toolkit for rapidly prototyping statistical models using dynamic graphical models (DGMs) and dynamic Bayesian networks (DBNs). GMTK can be used for applications and research in speech and language processing, bioinformatics, activity recognition, and any time series application. GMTK has many features, including exact and approximate inference; a large variety of built-in factors including dense, sparse, and deterministic conditional probability tables, native support for ARPA backoff-based factors and factored language models, parameter sharing, gamma and beta distributions, dense and sparse Gaussian factors, heterogeneous mixtures, deep neural network factors, and time-inhomogeneous trellis factors; arbitrary order embedded Markov chains; a GUI-based graph viewer; flexible feature-file support and processing tools (supporting pfiles, HTK files, ASCII/binary, and HDF5 files); and both offline and streaming online inference methods that can be used for both parameter learning and prediction. More information is available in the documentation. All in all, GMTK offers a flexible, concise, and expressive probabilistic modeling framework with which one may rapidly specify a vast collection of temporal statistical models.

Electronic downloads

Internal. This publication has been marked by the author for TerraSwarm-only distribution, so electronic downloads are not available without logging in.

Citation formats

• HTML

  Jeffrey A. Bilmes, Richard Rogers. <a
  href="http://www.terraswarm.org/pubs/503.html"
  ><i>GMTK: The Graphical Models
  Toolkit</i></a>, University of Washington, 10,
  February, 2015.

• Plain text

  Jeffrey A. Bilmes, Richard Rogers. "GMTK: The Graphical
  Models Toolkit". University of Washington, 10,
  February, 2015.

• BibTeX

  @software{BilmesRogers15_GMTKGraphicalModelsToolkit,
      author = {Jeffrey A. Bilmes and Richard Rogers},
      title = {GMTK: The Graphical Models Toolkit},
      institution = {University of Washington},
      day = {10},
      month = {February},
      year = {2015},
      abstract = {The Graphical Models Toolkit (GMTK) is an open
                source, publicly available toolkit for rapidly
                prototyping statistical models using dynamic
                graphical models (DGMs) and dynamic Bayesian
                networks (DBNs). GMTK can be used for applications
                and research in speech and language processing,
                bioinformatics, activity recognition, and any time
                series application. GMTK has many features,
                including exact and approximate inference; a large
                variety of built-in factors including dense,
                sparse, and deterministic conditional probability
                tables, native support for ARPA backoff-based
                factors and factored language models, parameter
                sharing, gamma and beta distributions, dense and
                sparse Gaussian factors, heterogeneous mixtures,
                deep neural network factors, and
                time-inhomogeneous trellis factors; arbitrary
                order embedded Markov chains; a GUI-based graph
                viewer; flexible feature-file support and
                processing tools (supporting pfiles, HTK files,
                ASCII/binary, and HDF5 files); and both offline
                and streaming online inference methods that can be
                used for both parameter learning and prediction.
                More information is available in the
                documentation. All in all, GMTK offers a flexible,
                concise, and expressive probabilistic modeling
                framework with which one may rapidly specify a
                vast collection of temporal statistical models.},
      URL = {http://terraswarm.org/pubs/503.html}
  }
  

Posted by Barb Hoversten on 10 Feb 2015.
Groups: tools