Abstract In this work, a consistency analysis of duration parameter for Mandarin speech is presented. Found by an inspection on the pronunciation process of human beings, the consistency can be interpreted as a high correlation of a warping curve between the spectrum and the prosody intra a syllable. Through three steps in the procedure of the consistency analysis, the HMM algorithm... In this work, a consistency analysis of duration parameter for Mandarin speech is presented. Found by an inspection on the pronunciation process of human beings, the consistency can be interpreted as a high correlation of a warping curve between the spectrum and the prosody intra a syllable. Through three steps in the procedure of the consistency analysis, the HMM algorithm is used firstly to decode HMM-state sequences within a syllable at the same time as to divide them into three segments. Secondly, based on a designated syllable, the vector quantization (VQ) with the LBG algorithm is used to train the VQ codebooks of each segment. Thirdly, the duration vector of each segment is encoded as an index by VQ codebooks, and then the probability of each possible path is evaluated as a prerequisite to analyze the consistency. It is demonstrated experimentally that a consistency is definitely acquired in case the syllable is located exactly in the same word. These results offer a research direction that the time warping process intra a syllable must be considered in a TTS system to improve the speech quality. Read More Read Less

Abstract The main goal of this paper is to compare the performance which can be achieved by two different hybrid approaches analyzing their applications’ potentiality on real world paradigms (speech recognition and medical diagnosis). We compare the performance obtained with (1) Multinetwork RBF/LVQ structure, we use involves Learning Vector Quantization (LVQ) as a competitive decision processor and Radial Basis Function (RBF)... The main goal of this paper is to compare the performance which can be achieved by two different hybrid approaches analyzing their applications’ potentiality on real world paradigms (speech recognition and medical diagnosis). We compare the performance obtained with (1) Multinetwork RBF/LVQ structure, we use involves Learning Vector Quantization (LVQ) as a competitive decision processor and Radial Basis Function (RBF) neural models is used as classifier. (2) Hybrid HMM/MLP system using a Multi Layer-Perceptron (MLP) to estimate the Hidden Markov Models (HMM) emission probabilities. Read More Read Less

Abstract The popularity of NoSQL databases (especially Cassandra) has been increasing day by day. Now, as many companies are developing Cassandra applications, they may need new tools to monitor database performance efficiently. Developers have difficulty optimizing something they can’t see. When problems related to performance occur and proper analysis is needed, the statistical data generated by monitoring tool will be of... The popularity of NoSQL databases (especially Cassandra) has been increasing day by day. Now, as many companies are developing Cassandra applications, they may need new tools to monitor database performance efficiently. Developers have difficulty optimizing something they can’t see. When problems related to performance occur and proper analysis is needed, the statistical data generated by monitoring tool will be of a lot help. To optimize NoSQL applications, developers need to have an idea about how the database is behaving in different working scenarios. Cassandra is easy to configure, but for the proper performance tuning it is necessary to study the performance requirements for a particular application. This can be judged by monitoring tool. The paper describes the design of such monitoring tool and the results generated ie. statistics and graphs. The tool will be used primarily for low end machines as they are cost effective. Read More Read Less

Abstract The aim of this work is to develop software to predict the value of yield and distribution coefficient in the process of reactive liquid-liquid extraction of chemicals components, using mathematical models expressing these entities, based on equations equilibrium between organic and aqueous phases, and predict the conditions under which the extraction operation is favorable, unfavorable or impossible to realize, by... The aim of this work is to develop software to predict the value of yield and distribution coefficient in the process of reactive liquid-liquid extraction of chemicals components, using mathematical models expressing these entities, based on equations equilibrium between organic and aqueous phases, and predict the conditions under which the extraction operation is favorable, unfavorable or impossible to realize, by studying the variation of the entities cited, based on the parameters influencing the extraction, which are: initial concentrations, rate of solvent and pH, in the case of a simple extraction (extraction of neutral products) or when it is reactive (extraction of complex acids or bases) for one or more components. The programming language used is “Delphi” which is a very powerful oriented object programming under Windows. Read More Read Less