Hmm Parameter Optimization Using Tabu Search
نویسندگان
چکیده
Hidden Markov Model (HMM) is regularly trained via mathematic functions optimized by gradient-based methods such as Baum-Welch (BW) algorithm. However, optimization from gradient-based methods usually yields only a local optimum. In this paper, Tabu search (TS), an artificial intelligent (AI) technique able to step back from a local optimum and search for other optima, is employed to attack this difficulty. This paper aims to utilize HMM with TS for speakerindependent (SI) continuous speech recognition. The experiment starts from single speaker experiment in order to design and adjust the algorithm. Then, multi-Gaussian context-dependent (CD) model is applied for SI system. The results show the merit of this new algorithm comparing with the original BW.
منابع مشابه
Comparison of particle swarm optimization and tabu search algorithms for portfolio selection problem
Using Metaheuristics models and Evolutionary Algorithms for solving portfolio problem has been considered in recent years.In this study, by using particles swarm optimization and tabu search algorithms we optimized two-sided risk measures . A standard exact penalty function transforms the considered portfolio selection problem into an equivalent unconstrained minimization problem. And in final...
متن کاملA Static Mapping Heuristic for Mapping Parallel Applications to Heterogeneous Computing Systems
To minimize the execution time of a parallel application running on a heterogeneous computing distributed system, an appropriate mapping scheme to allocate the application tasks to the processors is needed. The general problem of mapping tasks to machines is a well known NP-hard problem and several heuristics have been proposed to approximate its optimal solution. In this paper we propose a sta...
متن کاملHMM: A Static Mapping Algorithm to Map Parallel Applications on Grids
In this paper we present a static mapping heuristic, called Heterogeneous Multi-phase Mapping (HMM), which allows a suboptimal mapping of a parallel program onto a metacomputer to minimize the program execution time. HMM allocates parallel tasks by exploiting the information embedded in the parallelism forms used to implement an application. Moreover, it uses a local search technique together w...
متن کاملTabu-KM: A Hybrid Clustering Algorithm Based on Tabu Search Approach
The clustering problem under the criterion of minimum sum of squares is a non-convex and non-linear program, which possesses many locally optimal values, resulting that its solution often falls into these trap and therefore cannot converge to global optima solution. In this paper, an efficient hybrid optimization algorithm is developed for solving this problem, called Tabu-KM. It gathers the ...
متن کاملApplication of Intelligent Search Techniques to Identify Single-Phase Induction Motor’s Parameters
This paper presents an intelligent approach to identify parameters of single-phase induction motors. Because of the complication of space-phasor equations describing its dynamic behaviors, the parameters of single-phase induction motors could be roughly estimated via conventional tests based on the steady-state analysis. Therefore, they may cause inaccurate estimation. In this paper, some effic...
متن کامل