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中国科学院数学与系统科学研究院李雷研究团队的成果“基因组拼接的新方法—BAUM”入选2018年度“中国生物信息学十大进展”（图）
中国科学院数学与系统科学研究院 基因组 拼接方法 BAUM 2018年度
2019/2/26
近日，我院李雷研究团队发表于《生物信息学》期刊的文章“BAUM: improving genome assembly by adaptive unique mapping and local overlap-layout-consensus approach”，经《基因组蛋白质组与生物信息学报》，简称GPB（Genomics, Proteomics and Bioinformatics）评审，入选...
EXTENDED BAUM TRANSFORMATIONS FOR GENERAL FUNCTIONS, II
Multidimensional Multivariate Gaussuan Mixture Extended Baum-Welch transformations discriminative training estimation of statistical parameters maximum mutual informaiton estimation
2015/7/30
The discrimination technique for estimating the parameters of Gaussian mixtures that is based on the Extended Baum transformations (EB) has had significant impact on the speech recognition community. ...
Adapted Extended Baum-Welch transformations
MMIE training EBW transformations gradient steepness
2015/7/29
The discrimination technique for estimating parameters of Gaussian mixtures that is based on the Extended Baum-Welch transformations (EBW) has had significant impact on the speech recognition communit...
In this paper, we consider a generalization of the state-of-art discriminative method for optimizing the conditional likelihood in Hidden Markov Models (HMMs), called the Extended Baum-Welch (EBW) alg...
In this paper, we consider a generalization of the state-of-art discriminative method for optimizing the conditional likelihood in Hidden Markov Models (HMMs), called the Extended Baum-Welch (EBW) alg...
Generalization of Extended Baum-Welch Parameter Estimation for Discriminative Training and Decoding
Extended Baum-Welch optimization speech
2015/7/28
We demonstrate the generalizability of the Extended Baum-Welch (EBW) algorithm not only for HMM parameter estimation but for decoding as well. We show that there can exist a general function associate...
Baum-Welch Training for Segment-Based Speech Recognition
Baum-Welch Training Speech Recognition
2015/3/11
Baum-Welch Training for Segment-Based Speech Recognition.
Unsupervised Audio Segmentation Using Extended Baum-Welch Transformations
Acoustic signal detection gradient methods
2015/3/10
Unsupervised Audio Segmentation Using Extended Baum-Welch Transformations.
Audio Classification using the Extended Baum-Welch Transformations
Extended Baum-Welch Transformations Audio Classification
2015/3/10
Audio Classification using the Extended Baum-Welch Transformations.
Broad Phonetic Class Recognition in a Hidden Markov Model Framework Using Extended Baum-Welch Transformations
Gradient Methods Viterbi Decoding
2015/3/10
Broad Phonetic Class Recognition in a Hidden Markov Model Framework Using Extended Baum-Welch Transformations.
Gradient Steepness Metrics using Extended Baum-Welch Transformations for Universal Pattern Recognition Tasks
Pattern recognition gradient methods
2015/3/10
Gradient Steepness Metrics using Extended Baum-Welch Transformations for Universal Pattern Recognition Tasks.
Generalization of Extended Baum-Welch Parameter Estimation for Discriminative Training and Decoding
Discriminative Training Decoding
2015/3/10
Generalization of Extended Baum-Welch Parameter Estimation for Discriminative Training and Decoding.
BAUM-WELCH TRAINING FOR SEGMENT-BASED SPEECH RECOGNITION
BAUM-WELCH TRAINING SEGMENT-BASED SPEECH RECOGNITION.
2014/11/27
BAUM-WELCH TRAINING FOR SEGMENT-BASED SPEECH RECOGNITION.
Professor Tom Baum，Department of Human Resource Management at University of Strathclyde（图）
Professor Tom Baum Department of Human Resource Management at University of Strathclyde
2014/11/17
Tom Baum is academic interests address the social and strategic contexts of low skills employment, with particular focus on hospitality and tourism. This interest stems from over 30 years of experienc...
Regime Switching Volatility Calibration by the Baum-Welch Method
Regime switching stochastic volatility calibration Hamilton filter Baum-Welch
2010/10/29
Regime switching volatility models provide a tractable method of modelling stochastic volatility. Currently the most popular method of regime switching calibration is the Hamilton filter. We propose u...
