Nonlinear Statistical Modeling of Speech:

Hidden Markov models (HMMs) have been the primary approach to speech recognition for almost 25 years. The goal of this project is to develop a new approach to statistical modeling of speech based on nonlinear statistics using principles of chaos.

Our first step will be to implement a speaker recognition system using a nonlinear time series approach to modeling the signal. This approach will be compared to our previous attempts to advance HMMs based on Support Vector Machines (SVMs) and Relevance Vector Machines (RVMs).




Relevant Resources:

  • Overview: A brief description of what we hope to accomplish in this project.
  • Bibliography: A collection of relevant papers on this topic.
  • Downloads: Download the latest versions of our software, data, and evaluation scripts.
  • Publications: Access background information related to this project.
  • Results: Access the baseline experimental results.
  • Baseline Results: Access the baseline experimental results.


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