Showing 6 open source projects for "hidden"

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  • 1
    Kaldi

    Kaldi

    kaldi-asr/kaldi is the official location of the Kaldi project

    ...It provides a powerful framework for building state-of-the-art automatic speech recognition (ASR) systems, with support for deep neural networks, Gaussian mixture models, hidden Markov models, and other advanced techniques. The toolkit is widely used in both academia and industry due to its flexibility, extensibility, and strong community support. Kaldi is designed for researchers who need a highly customizable environment to experiment with new algorithms, as well as for practitioners who want robust, production-ready ASR pipelines. ...
    Downloads: 4 This Week
    Last Update:
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  • 2
    The General Hidden Markov Model Library (GHMM) is a C library with additional Python bindings implementing a wide range of types of Hidden Markov Models and algorithms: discrete, continous emissions, basic training, HMM clustering, HMM mixtures.
    Downloads: 1 This Week
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  • 3

    NeuroSolutions: Formula Generator

    Utility converts the weights file of a MLP Breadboard into a formula

    The NeuroSolutions: Formula Generator utility converts the weights file of a default MLP breadboard (1-hidden layer with a TanhAxon in the hidden layer and either a TanhAxon or BiasAxon in the output layer) into a usable formula that can be copied and pasted into your own programs to compute the output of the trained neural network.
    Downloads: 0 This Week
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  • 4
    The AK toolkit is another kit for building and use Hidden Markov Models (HMMs). Originally developed for handwritten text recognition (HTR) using Bernoulli HMMs, it also implements diagonal Gaussians and can be used for any other purpose.
    Downloads: 0 This Week
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  • 5
    ESMERALDA is a development environment for statistical recognizers operating on sequential data (speech, handwriting, biological sequences). It supports continuous density Hidden Markov models, Markov chain (N-gramm) models, and Gaussian mixture models.
    Downloads: 0 This Week
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  • 6
    This project will show how to implement the Hidden Markov Model approximations of Voice Recognition into embedded and low power systems.
    Downloads: 0 This Week
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