Results 31 to 40 of about 41,241 (143)
Dynamic Bayesian Networks for Audio-Visual Speech Recognition
EURASIP Journal on Advances in Signal Processing, 2002 The use of visual features in audio-visual speech recognition (AVSR) is justified by both the speech generation mechanism, which is essentially bimodal in audio and visual representation, and by the need for features that are invariant to acoustic noise
Liang Luhong +4 more
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Using Hidden Markov Chains in Recognition of Vowel Letters in English Language [PDF]
المجلة العراقية للعلوم الاحصائية, 2006 This study deals with hidden Markov models . These models consist of sets of finite states , each one of them is associated with a probability distribution .
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Hidden Semi Markov Models for Multiple Observation Sequences: The mhsmm Package for R
Journal of Statistical Software, 2011 This paper describes the R package mhsmm which implements estimation and prediction methods for hidden Markov and semi-Markov models for multiple observation sequences. Such techniques are of interest when observed data is thought to be dependent on some
Jared O'Connell, Søren Højsgaard
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Enhancing Botnet Detection in Network Security Using Profile Hidden Markov Models
Applied SciencesA botnet is a network of compromised computer systems, or bots, remotely controlled by an attacker through bot controllers. This covert network poses a threat through large-scale cyber attacks, including phishing, distributed denial of service (DDoS ...
Rucha Mannikar, Fabio Di Troia
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Hidden Markov models: Pitfalls and opportunities in ecology
Methods in Ecology and Evolution, 2023 Hidden Markov models (HMMs) and their extensions are attractive methods for analysing ecological data where noisy, multivariate measurements are made of a hidden, ecological process, and where this hidden process is represented by a sequence of discrete ...
Richard Glennie +5 more
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ADAPTIVE LEARNING OF HIDDEN MARKOV MODELS FOR EMOTIONAL SPEECH
Informatika, 2016 An on-line unsupervised algorithm for estimating the hidden Markov models (HMM) parame-ters is presented. The problem of hidden Markov models adaptation to emotional speech is solved.
A. V. Tkachenia
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International Journal of Advanced Robotic Systems, 2019 Robot introspection aids robots to understand what they do and how they do it. Previous robot introspection techniques have often used parametric hidden Markov models or supervised learning techniques, implying that the number of hidden states or classes
Hongmin Wu, Yisheng Guan, Juan Rojas
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HIPPI: highly accurate protein family classification with ensembles of HMMs
BMC Genomics, 2016 Background Given a new biological sequence, detecting membership in a known family is a basic step in many bioinformatics analyses, with applications to protein structure and function prediction and metagenomic taxon identification and abundance ...
Nam-phuong Nguyen +3 more
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Hidden Markov models applied to a subsequence of the Xylella fastidiosa genome
Genetics and Molecular Biology, 2003 Dependencies in DNA sequences are frequently modeled using Markov models. However, Markov chains cannot account for heterogeneity that may be present in different regions of the same DNA sequence.
Silva Cibele Q. da
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Hidden Markov Models in Speech Recognition
Advances in Electrical and Electronic Engineering, 2008 Voice control is one of the perspective areas of interdisciplinary field called Human Machine Interface (HMI). By the voice control of machines, we usually deal with the recognition of commands from previously defined set.
Jan Krajcovic +2 more
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