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Showing 1 to 11 of 11 for “"Baum Welch"”.

  1. Experiments with hidden Markov models

    … chains with generative transitions and the Baum-Welch algorithm. We explore generating the hypothesis model in various ways. We use the hypothesis model as the original model. And we investigate the feasibility of implementing a sequential version of the Baum-Welch algorithm. This research …

    reykjavik Repository record for Experiments with hidden Markov models (opens in a new tab)

  2. Two new approaches for learning Hidden Markov Models

    … to infer these hidden variables has been the Baum-Welch algorithm. This thesis utilizes insights from two related fields. The first insight is from Angluin's seminal paper on learning regular sets from queries and counterexamples, which produces a simple and intuitive algorithm that …

    mit Repository record for Two new approaches for learning Hidden Markov Models (opens in a new tab)

  3. Automatic Phoneme Recognition with Segmental Hidden Markov Models

    … (HMM) based phoneme models are trained using the Baum-Welch re-estimation procedure. Recognition and segmentation of the phonemes in the continuous speech is performed by a Segmental Viterbi Search on a Segmental Ergodic HMM for the phoneme states. We describe in detail the three phases of the …

    vt Repository record for Automatic Phoneme Recognition with Segmental Hidden Markov Models (opens in a new tab)

  4. One-vector representations of stochastic signals for pattern recognition

    … for HMMs, which we refer to as the boosting Baum-Welch algorithm. In the proposed boosting Baum-Welch algorithm, we formulate the HMM learning problem as an incremental optimization procedure which performs a sequential gradient descent search on a loss functional for a good fit in an inner …

    uiuc Repository record for One-vector representations of stochastic signals for pattern recognition (opens in a new tab)

  5. Parameter estimation in HMMs with guaranteed convergence

    … The EM algorithm for HMMs, also known as the Baum-Welch algorithm, was previously studied by Yang, Balakrishnan, and Wainwright [1] but without global convergence guarantees. In this paper we propose a "local" version of the EM algorithm and prove absolute convergence of this algorithm to the …

    mit Repository record for Parameter estimation in HMMs with guaranteed convergence (opens in a new tab)

  6. Applying binary decision diagrams to learn hidden Markov models

    … of Hidden Markov Models, by building upon the Baum-Welch (BW) algorithm’s methodology. EM-BDD utilises the Forward-Backward procedure, a cornerstone of BW, adapting it to operate on Binary Decision Diagrams (BDDs). The time and memory complexity of the algorithm is contingent on the size of the …

    reykjavik Repository record for Applying binary decision diagrams to learn hidden Markov models (opens in a new tab)

  7. A uniform representation for visual concepts

    … in videos. We use a discriminative variant of Baum-Welch to learn the parameters for our word models, and demonstrate that our approach is able to learn words capturing appearance, spatial relations, and temporal dynamics.

    mit Repository record for A uniform representation for visual concepts (opens in a new tab)

  8. An integrated performance model learning and planning approach for optimal infrastructure facility maintenance under partial observability

    … estimate of performance model using the Baum-Welch algorithm. Both offline and online versions of the learning algorithm are presented. The probing-optimizing dichotomy, also known as exploration-exploitation dilemma, in choosing between the best strategy based on the past knowledge of …

    tdl Repository record for An integrated performance model learning and planning approach for optimal infrastructure facility maintenance under partial observability (opens in a new tab)

  9. Android Application Install-time Permission Validation and Run-time Malicious Pattern Detection

    … size by adding game applications, to optimize Baum-Welch algorithm parameters, and to balance the size of the Intent sequence. To better emulate the participant's usage, some popular applications can be selected in advance, and the remainder can be randomly chosen.

    vt Repository record for Android Application Install-time Permission Validation and Run-time Malicious Pattern Detection (opens in a new tab)

  10. Applications of broad class knowledge for noise robust speech recognition

    … a gradient steepness metric using the Extended Baum-Welch (EBW) transformations to explain how much these initial model must be adapted to fit the target data. We incorporate this gradient metric into a Hidden Markov Model (HMM) framework for broad class recognition and illustrate that this …

    mit Repository record for Applications of broad class knowledge for noise robust speech recognition (opens in a new tab)

  11. Iterative Decoding and Channel Estimation over Hidden Markov Fading Channels

    Since the 1950s, hidden Markov models (HMMS) have seen widespread use in electrical engineering. Foremost has been their use in speech processing, pattern recognition, artificial intelligence, queuing theory, and communications theory. However, recent years have witnessed a renaissance in the …

    vt Repository record for Iterative Decoding and Channel Estimation over Hidden Markov Fading Channels (opens in a new tab)