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Revolutionizing Stem Cell Sorting with Machine Learning: A Review of Trends, Tools, and Future Directions. [PDF]
Iran J Med SciMousazadeh M +6 more
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On semi-continuous hidden Markov modeling
International Conference on Acoustics, Speech, and Signal Processing, 2002The semicontinuous hidden Markov model is used in a 1000-word speaker-independent continuous speech recognition system and compared with the continuous mixture model and the discrete model. When the acoustic parameter is not well modeled by the continuous probability density, it is observed that the model assumption problems may cause the recognition ...
Xuedong Huang 0001 +2 more
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Hidden semi-Markov model for anomaly detection
Applied Mathematics and Computation, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xiaobin Tan, Hongsheng Xi
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Revisiting semi-continuous hidden Markov models
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012In the past decade, semi-continuous hidden Markov models (SCHMMs) have not attracted much attention in the speech recognition community. Growing amounts of training data and increasing sophistication of model estimation led to the impression that continuous HMMs are the best choice of acoustic model.
Korbinian Riedhammer +3 more
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Hidden semi-Markov model based speech synthesis
Interspeech 2004, 2004In the present paper, a hidden-semi Markov model (HSMM) based speech synthesis system is proposed. In a hidden Markov model (HMM) based speech synthesis system which we have proposed, rhythm and tempo are controlled by state duration probability distributions modeled by single Gaussian distributions.
Heiga Zen +4 more
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Semi-hidden Markov models for generation and analysis of sequences
Mathematics and Computers in Simulation, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
R. Román-Gálvez +3 more
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The evaluation problem in discrete semi-hidden Markov models
Mathematics and Computers in Simulation, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Juan Francisco Gómez-Lopera +4 more
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Modeling state duration and emission dependence in hidden Markov and hidden semi-Markov models
2023Hidden Markov models (HMM) are composed of a latent state sequence and an observation sequence conditionally independent on the states, which follows an emission distribution. Hidden semi-Markov models (HSMM) extend the HMM by explicitly modeling the duration in the states.
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Hidden semi-Markov models for electricity load disaggregation
ACM SIGMETRICS Performance Evaluation Review, 2019This paper assesses the performance of a technique for estimating the power consumption of individual devices based on aggregate consumption. The new semi-Markov technique, outperforms pure hidden Markov models on the REDD dataset. The technique also exploits information from transients to eliminate a substantial fraction of the observed ...
Yung Fei Wong +2 more
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