Informatica

This paper presents a new approach for the business and information systems (IS) alignment consisting of a framework, metamodel, process, and tools for implementing it in practice. The purpose of the approach is to fill in the gap between the existing conceptual business and IS alignment frameworks and the empirical business and IS alignment methods. The suggested approach is based on the SOA, GRAAL, and enterprise modeling techniques such as TOGAF, DoDAF, and UPDM. The proposed approach is applied on four real world projects. Both the application results and the small example are provided to validate the suitability of the approach.

Specifics of hidden Markov model‐based speech recognition are investigated. Influence of modeling simple and context‐dependent phones, using simple Gaussian, two and three‐component Gaussian mixture probability density functions for modeling feature distribution, and incorporating language model are discussed. Word recognition rates and model complexity criteria are used for evaluating suitability of these modifications for practical applications. Development of large vocabulary continuous speech recognition system using HTK toolkit and WSJCAM0 English speech corpus is described. Results of experimental investigations are presented.