The use of adaptation transforms common in speech recognition systems as features for speaker recognition is an appealing alternative approach to conventional short-term cepstral modelling of speaker characteristics. Recently, we have shown that it is possible to use transformation weights derived from adaptation techniques applied to the Multi Layer Perceptrons that form a connectionist speech...

We present a clustering method for collections of graphs based on the assumptions that graphs in the same cluster have a similar role structure and that the respective roles can be founded on implicit vertex types. Given a network ensemble (a collection of attributed graphs with some substantive commonality), we start by partitioning the set of all vertices based on attribute similarity. Projec...

Databases ometimes have keys besides those pre-planned by the database designers. These are easy to discover given functional dependencies in the data. These superfluous keys are convenient ira user wishes to add data to a projection of the database. A key can be chosen that minimizes the attributes the user must edit. In a list format view, enough attribute columns are added to those specified...

An adjoint-based output error estimation algorithm is presented for unsteady problems discretized on static meshes with a space-time discontinuous Galerkin finite element method. An approximate factorization technique is used to solve both the forward and the discrete adjoint problems. A space-time anisotropy measure based on projection of the adjoint solution is used to attribute the error to ...

Recent reviews have concluded that efforts to date have yet to detect or attribute an anthropogenic climate change influence on Atlantic tropical cyclone (of at least tropical storm strength) behaviour and concomitant damage. However, the possibility of identifying such influence in the future cannot be ruled out. Using projections of future tropical cyclone activity from a recent prominent stu...

The attribute selection techniques for supervised learning, used in the preprocessing phase to emphasize the most relevant attributes, allow making models of classification simpler and easy to understand. The algorithm (SOAP: Selection of Attributes by Projection) has some interesting characteristics: lower computational cost (O(m n log n) m attributes and n examples in the data set) with respe...

The relationship between redundancy elimination and normal forms in relational database design is investigated for the case where the constraints contain functional dependencies (FDs) and arbitrary join dependencies (JDs). Extending previous work on the relationship between fourth normal form (4NF) and redundancy elimination, a general definition of redundancy is proposed which is applicable to...

Robust speaker verification on short utterances remains a key consideration when deploying automatic speaker recognition, as many real world applications often have access to only limited duration speech data. This paper explores how the recent technologies focused around total variability modeling behave when training and testing utterance lengths are reduced. Results are presented which provi...

The Nuisance Attribute Project (NAP) with labeled data provides an effective approach for improving the speaker recognition performance in the state-of-art speaker recognition system by removing unwanted channel and handset variation. However, the requirement for the labeled NAP training data may limit its practical application. In our previous study, a simple unsupervised clustering algorithm ...