Abstract In this paper, we propose a supervised single-channel speech enhancement method that combines Kullback-Leibler (KL) divergence-based non-negative matrix factorization (NMF) and hidden Markov model (NMF-HMM). With the integration of HMM, temporal dynamics information signals can be taken into account. This includes training stage an stage. stage, sum Poisson distribution, leading to KL ...

In this paper, hidden semi-Markov model (HSMM) is introduced into intrusion detection. Hidden Markov model (HMM) has been applied in intrusion detection systems several years, but it has a major weakness: the inherent duration probability density of a state in HMM is exponential, which may be inappropriate for the modeling of audit data of computer systems. We can handle this problem well by de...

To shed light on the question whether humans converge phonetically to synthesized speech, a shadowing experiment was conducted using three different types of stimuli – natural speaker, diphone synthesis, and HMM synthesis. Three segment-level phonetic features of German that are well-known to vary across native speakers were examined. The first feature triggered convergence in roughly one third...

Chromosomal DNA is characterized by variation between individuals at the level of entire chromosomes (e.g. aneuploidy in which the chromosome copy number is altered), segmental changes (including insertions, deletions, inversions, and translocations), and changes to small genomic regions (including single nucleotide polymorphisms). A variety of alterations that occur in chromosomal DNA, many of...

MOTIVATION Copy number profiling methods aim at assigning DNA copy numbers to chromosomal regions using measurements from microarray-based comparative genomic hybridizations. Among the proposed methods to this end, Hidden Markov Model (HMM)-based approaches seem promising since DNA copy number transitions are naturally captured in the model. Current discrete-index HMM-based approaches do not, h...

Array-based technologies have been used to detect chromosomal copy number changes (aneuploidies) in the human genome. Recent studies identified numerous copy number variants (CNV) and some are common polymorphisms that may contribute to disease susceptibility. We developed, and experimentally validated, a novel computational framework (QuantiSNP) for detecting regions of copy number variation f...

1.1 New training methods for the HMMs The training of the context-independent phoneme models for a minimal recognition error rate is diicult, because the variability of the phonemes in diierent conditions and contexts is substantial and the output densities of diierent phonemes do also overlap. A structure that can automatically adapt to all the complicated density functions, has a vast number ...

The classical HMM is defined by a parameter triple λ = (π, A, B), where each represents collection of probability distributions: initial state, state transition and output distributions in order. This paper proposes new stationary e =(e1,e2,…,e<sub...