This paper presents a computational algorithm for machine classification of written languages using the Markov chain-based method for building language models and the fuzzy set theory-based normalization method to verify language. For a language document, each word is represented as a Markov chain of alphabetical letters. The initial probability and transition probabilities are calculated and the set of such probabilities obtained from the training data is referred to as the model of that language. Given an unknown text document and a claimed identity of a language, a similarity score based on fuzzy set theory is calculated and compared with a preset threshold. If the match is good enough, the identity claim is accepted. The proposed fuzzy ...
In this paper, a method for analytic handwritten word recognition based on causal Markov random fiel...
This paper incorporates statistical language models into an on-line handwriting recognition system f...
Automatic Speech Recognition (ASR) systems utilize statistical acoustic and language models to find ...
This paper presents a computational algorithm for machine classification of written languages using ...
In this paper, we compare the performance of several Markovian time series models for language ident...
In classifying handwritten characters, the stages prior to the classification phase play a role as m...
Two major stages stages in language identification systems can be identified: the language modeling ...
We explain how to apply statistical techniques to solve several language-recognition problems that a...
this paper, I discuss the use of two techniques to perform automatic language classification. The fi...
In this bachelor’s thesis, we try to classify and identify written human languages by studying the o...
This paper describes two methods of language identification, both of which are based on HMMs(Hidden ...
We present a statistical approach to text-based automatic language identification that focuses on di...
Hidden Markov models are used to model the generation of handwritten, isolated characters. Models ar...
Research in off-line handwriting recognition has been prevalent for many decades. After many years o...
A linguistic recognition system based on approximate reasoning has been described which is capable o...
In this paper, a method for analytic handwritten word recognition based on causal Markov random fiel...
This paper incorporates statistical language models into an on-line handwriting recognition system f...
Automatic Speech Recognition (ASR) systems utilize statistical acoustic and language models to find ...
This paper presents a computational algorithm for machine classification of written languages using ...
In this paper, we compare the performance of several Markovian time series models for language ident...
In classifying handwritten characters, the stages prior to the classification phase play a role as m...
Two major stages stages in language identification systems can be identified: the language modeling ...
We explain how to apply statistical techniques to solve several language-recognition problems that a...
this paper, I discuss the use of two techniques to perform automatic language classification. The fi...
In this bachelor’s thesis, we try to classify and identify written human languages by studying the o...
This paper describes two methods of language identification, both of which are based on HMMs(Hidden ...
We present a statistical approach to text-based automatic language identification that focuses on di...
Hidden Markov models are used to model the generation of handwritten, isolated characters. Models ar...
Research in off-line handwriting recognition has been prevalent for many decades. After many years o...
A linguistic recognition system based on approximate reasoning has been described which is capable o...
In this paper, a method for analytic handwritten word recognition based on causal Markov random fiel...
This paper incorporates statistical language models into an on-line handwriting recognition system f...
Automatic Speech Recognition (ASR) systems utilize statistical acoustic and language models to find ...