An a priori Indicator of the Discrimination Power of Discrete Hidden Markov Models
نویسندگان
چکیده
During the development of a hidden Markov modelbased handwriting recognition system, the testing phase takes a non-negligible amount of computation time. This is especially true for real application where the lexicon size is large. In order to shorten the development process we propose an indicator of the system discrimination power. This indicator is calculated during training and its final value is obtained at the end of the training phase, without more calculation. Its definition consists of a modification of the observation probability of the validation corpus by the trained system. Some experiments were carried out and the results show clearly the correlation between this indicator and recognition rates.
منابع مشابه
Introducing Busy Customer Portfolio Using Hidden Markov Model
Due to the effective role of Markov models in customer relationship management (CRM), there is a lack of comprehensive literature review which contains all related literatures. In this paper the focus is on academic databases to find all the articles that had been published in 2011 and earlier. One hundred articles were identified and reviewed to find direct relevance for applying Markov models...
متن کاملSpeech enhancement based on hidden Markov model using sparse code shrinkage
This paper presents a new hidden Markov model-based (HMM-based) speech enhancement framework based on the independent component analysis (ICA). We propose analytical procedures for training clean speech and noise models by the Baum re-estimation algorithm and present a Maximum a posterior (MAP) estimator based on Laplace-Gaussian (for clean speech and noise respectively) combination in the HMM ...
متن کاملRelative Entropy Rate between a Markov Chain and Its Corresponding Hidden Markov Chain
In this paper we study the relative entropy rate between a homogeneous Markov chain and a hidden Markov chain defined by observing the output of a discrete stochastic channel whose input is the finite state space homogeneous stationary Markov chain. For this purpose, we obtain the relative entropy between two finite subsequences of above mentioned chains with the help of the definition of...
متن کاملAn Adaptive Approach to Increase Accuracy of Forward Algorithm for Solving Evaluation Problems on Unstable Statistical Data Set
Nowadays, Hidden Markov models are extensively utilized for modeling stochastic processes. These models help researchers establish and implement the desired theoretical foundations using Markov algorithms such as Forward one. however, Using Stability hypothesis and the mean statistic for determining the values of Markov functions on unstable statistical data set has led to a significant reducti...
متن کاملA new approach to wind turbine power generation forecasting, using weather radar data based on Hidden Markov Model
The wind is one of the most important and affecting phenomena and is known as one of the significant clean resources of energy. Apart from other atmospheric parameters, the wind has complex behavior and intermittent characteristics. Local phenomena can be accompanied by the wind, which is strong, non-predicted, and damaging. Weather radars are capable of detecting and displaying storm-related ...
متن کامل