Self-Organizing-Maps With BIC For Speaker Clustering

A new approach is presented for clustering the speakers from unlabeled and unsegmented conversation, when the number of speakers is unknown. In this approach, each speaker is modeled by a Self- Organizing-Map (SOM). For estimation of the number of clusters the Bayesian Information Criterion (BIC) is applied. This approach was tested on the NIST 1996 HUB-4 evaluation test in terms of speaker and cluster purities. Results indicate that the combined SOM-BIC approach can lead to better clustering results than the baseline system

What is Better: GMM of Two Gaussians or Two Clusters With One Gaussian?

In this report, we provide a theoretical discussion on temporal data cluster analysis: does the data come from one source or two sources; is it better to cluster the data into two clusters or leave it as one cluster. Here we analyse only the simplest case: when the data comes from two symmetric Gaussian probability-density-functions (pdfs), i.e., with same variance and same absolute value of the mean, with the same prior probability per Gaussian. The data consists of segments with an a-priori known segment length. It will be shown that if the data belongs to two different Gaussian models, the likelihood of two clusters is always higher or equal than the one of a GMM with two Gaussians for any mean, variance, and segment length. If the data belongs to the GMM, the likelihood of two clusters might be either higher or less than the GMM one

Extended BIC Criterion for Model Selection

Model selection is commonly based on some variation of the BIC or minimum message length criteria, such as MML and MDL. In either case the criterion is split into two terms: one for the model (data code length/model complexity) and one for the data given the model (message length/data likelihood). For problems such as change detection, unsupervised segmentation or data clustering it is common practice for the model term to comprise only a sum of sub-model terms. In this paper it is shown that the full model complexity must also take into account the number of sub models and the labels which assign data to each sub model. From this analysis we derive an extended BIC approach (EBIC) for this class of problem. Results with artificial data are given to illustrate the properties of this procedure

Dichotomy Between Clustering Performance and Minimum Distortion in Piecewise-Dependent-Data (PDD) Clustering

In many signal such speech, bio-signals, protein chains, etc. there is a dependency between consecutive vectors. As the dependency is limited in duration such data can be called as Piecewise-Dependent- Data (PDD). In clustering it is frequently needed to minimize a given distance function. In this paper we will show that in PDD clustering there is a contradiction between the desire for high resolution (short segments and low distance) and high accuracy (long segments and high distortion), i.e. meaningful clustering

Unknown-Multiple Speaker clustering using HMM

An HMM-based speaker clustering framework is presented, where the number of speakers and segmentation boundaries are unknown \emph{a priori}. Ideally, the system aims to create one pure cluster for each speaker. The HMM is ergodic in nature with a minimum duration topology. The final number of clusters is determined automatically by merging closest clusters and retraining this new cluster, until a decrease in likelihood is observed. In the same framework, we also examine the effect of using only the features from highly voiced frames as a means of improving the robustness and computational complexity of the algorithm. The proposed system is assessed on the 1996 HUB-4 evaluation test set in terms of both cluster and speaker purity. It is shown that the number of clusters found often correspond to the actual number of speakers

Lentiviral Vector Delivery of Human Interleukin-7 (hIL-7) to Human Immune System (HIS) Mice Expands T Lymphocyte Populations

Genetically modified mice carrying engrafted human tissues provide useful models to study human cell biology in physiologically relevant contexts. However, there remain several obstacles limiting the compatibility of human cells within their mouse hosts. Among these is inadequate cross-reactvitiy between certain mouse cytokines and human cellular receptors, depriving the graft of important survival and growth signals. To circumvent this problem, we utilized a lentivirus-based delivery system to express physiologically relevant levels of human interleukin-7 (hIL-7) in Rag2-/-γc-/- mice following a single intravenous injection. hIL-7 promoted homeostatic proliferation of both adoptively transferred and endogenously generated T-cells in Rag2-/-γc-/- Human Immune System (HIS) mice. Interestingly, we found that hIL-7 increased T lymphocyte numbers in the spleens of HIV infected HIS mice without affecting viral load. Taken together, our study unveils a versatile approach to deliver human cytokines to HIS mice, to both improve engraftment and determine the impact of cytokines on human diseases

Crowd Verifiable Zero-Knowledge and End-to-end Verifiable Multiparty Computation

Auditing a secure multiparty computation (MPC) protocol entails the validation of the protocol transcript by a third party that is otherwise untrusted. In this work, we introduce the concept of end-to-end verifiable MPC (VMPC), that requires the validation to provide a correctness guarantee even in the setting that all servers, trusted setup primitives and all the client systems utilized by the input-providing users of the MPC protocol are subverted by an adversary. To instantiate VMPC, we introduce a new concept in the setting of zero-knowlegde protocols that we term crowd verifiable zero-knowledge (CVZK). A CVZK protocol enables a prover to convince a set of verifiers about a certain statement, even though each one individually contributes a small amount of entropy for verification and some of them are adversarially controlled. Given CVZK, we present a VMPC protocol that is based on discrete-logarithm related assumptions. At the high level of adversity that VMPC is meant to withstand, it is infeasible to ensure perfect correctness, thus we investigate the classes of functions and verifiability relations that are feasible in our framework, and present a number of possible applications the underlying functions of which can be implemented via VMPC

The polo-like kinase 1 (PLK1) inhibitor NMS-P937 is effective in a new model of disseminated primary CD56+ acute monoblastic leukaemia

CD56 is expressed in 15–20% of acute myeloid leukaemias (AML) and is associated with extramedullary diffusion, multidrug resistance and poor prognosis. We describe the establishment and characterisation of a novel disseminated model of AML (AML-NS8), generated by injection into mice of leukaemic blasts freshly isolated from a patient with an aggressive CD56+ monoblastic AML (M5a). The model reproduced typical manifestations of this leukaemia, including presence of extramedullary masses and central nervous system involvement, and the original phenotype, karyotype and genotype of leukaemic cells were retained in vivo. Recently Polo-Like Kinase 1 (PLK1) has emerged as a new candidate drug target in AML. We therefore tested our PLK1 inhibitor NMS-P937 in this model either in the engraftment or in the established disease settings. Both schedules showed good efficacy compared to standard therapies, with a significant increase in median survival time (MST) expecially in the established disease setting (MST = 28, 36, 62 days for vehicle, cytarabine and NMS-P937, respectively). Importantly, we could also demonstrate that NMS-P937 induced specific biomarker modulation in extramedullary tissues. This new in vivo model of CD56+ AML that recapitulates the human tumour lends support for the therapeutic use of PLK1 inhibitors in AML

Eradication of chronic myeloid leukemia stem cells: a novel mathematical model predicts no therapeutic benefit of adding G-CSF to imatinib

Imatinib mesylate induces complete cytogenetic responses in patients with chronic myeloid leukemia (CML), yet many patients have detectable BCR-ABL transcripts in peripheral blood even after prolonged therapy. Bone marrow studies have shown that this residual disease resides within the stem cell compartment. Quiescence of leukemic stem cells has been suggested as a mechanism conferring insensitivity to imatinib, and exposure to the Granulocyte-Colony Stimulating Factor (G-CSF), together with imatinib, has led to a significant reduction in leukemic stem cells in vitro. In this paper, we design a novel mathematical model of stem cell quiescence to investigate the treatment response to imatinib and G-CSF. We find that the addition of G-CSF to an imatinib treatment protocol leads to observable effects only if the majority of leukemic stem cells are quiescent; otherwise it does not modulate the leukemic cell burden. The latter scenario is in agreement with clinical findings in a pilot study administering imatinib continuously or intermittently, with or without G-CSF (GIMI trial). Furthermore, our model predicts that the addition of G-CSF leads to a higher risk of resistance since it increases the production of cycling leukemic stem cells. Although the pilot study did not include enough patients to draw any conclusion with statistical significance, there were more cases of progression in the experimental arms as compared to continuous imatinib. Our results suggest that the additional use of G-CSF may be detrimental to patients in the clinic