Feature Selection for Hidden Markov Models and Hidden Semi-Markov Models
IEEE Access, 2016 In this paper, a joint feature selection and parameter estimation algorithm is presented for hidden Markov models (HMMs) and hidden semi-Markov models (HSMMs).
Stephen Adams +2 more
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Detection of sedentary time and bouts using consumer-grade wrist-worn devices: a hidden semi-Markov model [PDF]
BMC Medical Research MethodologyBackground Wrist-worn data from commercially available devices has potential to characterize sedentary time for research and for clinical and public health applications.
Agus Salim +11 more
doaj +2 more sources
Seasonal movement behavior of domestic goats in response to environmental variability and time of day using Hidden Markov Models [PDF]
Movement EcologyBackground Current research on livestock movement ecology focuses on quantifying the factors that trigger alterations in movement behavior and understanding hidden mechanisms.
Hua Cheng +4 more
doaj +2 more sources
Automatic Harmonization Using a Hidden Semi-Markov Model
Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2013 Hidden Markov Models have been used frequently in the audio domain to identify underlying musical structure. Much less work has been done in the purely symbolic realm. Recently, a substantial amount of expert-labelled symbolic musical data has been injected into the research community.
Ryan Groves
openalex +3 more sources
Hidden Markov Model of System Elements Technical Maintenance by Age [PDF]
E3S Web of Conferences, 2020 Technical maintenance is between the methods of operation reliability and effectiveness increasing for systems of different purposes including power systems.
Obzherin Yuriy +2 more
doaj +1 more source
Heavy tailed hidden semi-markov models [PDF]
Communications in Statistics. Stochastic Models, 1998 Summary: Hidden semi-Markov models have been proposed by \textit{K. S. Meier-Hellstern}, \textit{P. E. Wirth}, \textit{Y. L. Yan} and \textit{D. A. Hoeflin} [in: Teletraffic and datatraffic in a period of change (A. Jensen and V. B. Iversen (eds.)), 167-192 (1991)] to model the times between transmission of packets at a source.
Resnick, Sidney, Subramanian, Ajay
openaire +1 more source
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2021 Hidden Markov model (HMM) has been a popular choice for financial time series modeling due to its advantage in capturing dynamic regimes. However, HMM's implicit assumption that the state duration follows a geometric distribution is too strong to hold in
Zekun Xu, Ye Liu
doaj +1 more source
Improving Phoneme Sequence Recognition using Phoneme Duration Information in DNN-HSMM [PDF]
Journal of Artificial Intelligence and Data Mining, 2019 Improving phoneme recognition has attracted the attention of many researchers due to its applications in various fields of speech processing. Recent research achievements show that using deep neural network (DNN) in speech recognition systems ...
M. Asadolahzade Kermanshahi +1 more
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Use of Automation Technologies and Data Mining in Speech Recognition for Autism. [PDF]
Brain BehavPipeline analyzes clinical and naturalistic speech using LENA, wav2vec 2.0, and foundation‐model ASR (Whisper) to enable scalable ASD detection and severity estimation. Future work integrates benchmarking, privacy‐preserving collaboration (federated learning), and explainable, edge‐ready AI for clinically credible assessment and longitudinal monitoring.
Mao R, Zhu Y.
europepmc +2 more sources
Prediction of PM2.5 pollution in Tehran air based on temperature and pressure using Markovian regime-switching non-parametric additive transitive regression model [PDF]
ریاضی و جامعه, 2023 In this paper, we introduce the Markovian regime-switching regression model, which is a graphical model based on the hidden Markov model. This model can be viewed as a clustered regression model, in which a Markov process models the transition from one ...
Morteza Amini
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