#26499In optical character recognition and continuous speech recognition of a natural language, it has been difficult to detect error characters which are wrongly deleted and inserted.
tech,5-1-C94-1030,ak
optical character recognition
</term>
and
<term>
continuous speech recognition
</term>
of a
<term>
natural language
</term>
#26503In optical character recognition and continuous speech recognition of a natural language, it has been difficult to detect error characters which are wrongly deleted and inserted.
other,10-1-C94-1030,ak
continuous speech recognition
</term>
of a
<term>
natural language
</term>
, it has been difficult to detect
#26508In optical character recognition and continuous speech recognition of a natural language, it has been difficult to detect error characters which are wrongly deleted and inserted.
other,19-1-C94-1030,ak
, it has been difficult to detect
<term>
error characters
</term>
which are wrongly deleted and inserted
#26517In optical character recognition and continuous speech recognition of a natural language, it has been difficult to detect error characters which are wrongly deleted and inserted.
other,8-2-C94-1030,ak
order to judge three types of the
<term>
errors
</term>
, which are
<term>
characters
</term>
#26534In order to judge three types of the errors , which are characters wrongly substituted, deleted or inserted in a Japanese bunsetsu and an English word, and to correct these errors, this paper proposes new methods using m-th order Markov chain model for Japanese kanji-kana characters and English alphabets, assuming that Markov probability of a correct chain of syllables or kanji-kana characters is greater than that of erroneous chains.
other,12-2-C94-1030,ak
the
<term>
errors
</term>
, which are
<term>
characters
</term>
wrongly substituted , deleted or
#26538In order to judge three types of the errors, which are characters wrongly substituted, deleted or inserted in a Japanese bunsetsu and an English word, and to correct these errors, this paper proposes new methods using m-th order Markov chain model for Japanese kanji-kana characters and English alphabets, assuming that Markov probability of a correct chain of syllables or kanji-kana characters is greater than that of erroneous chains.
other,21-2-C94-1030,ak
substituted , deleted or inserted in a
<term>
Japanese bunsetsu
</term>
and an
<term>
English word
</term>
,
#26547In order to judge three types of the errors, which are characters wrongly substituted, deleted or inserted in a Japanese bunsetsu and an English word, and to correct these errors, this paper proposes new methods using m-th order Markov chain model for Japanese kanji-kana characters and English alphabets, assuming that Markov probability of a correct chain of syllables or kanji-kana characters is greater than that of erroneous chains.
other,25-2-C94-1030,ak
<term>
Japanese bunsetsu
</term>
and an
<term>
English word
</term>
, and to correct these
<term>
errors
#26551In order to judge three types of the errors, which are characters wrongly substituted, deleted or inserted in a Japanese bunsetsu and an English word, and to correct these errors, this paper proposes new methods using m-th order Markov chain model for Japanese kanji-kana characters and English alphabets, assuming that Markov probability of a correct chain of syllables or kanji-kana characters is greater than that of erroneous chains.
other,32-2-C94-1030,ak
word
</term>
, and to correct these
<term>
errors
</term>
, this paper proposes new methods
#26558In order to judge three types of the errors, which are characters wrongly substituted, deleted or inserted in a Japanese bunsetsu and an English word, and to correct these errors , this paper proposes new methods using m-th order Markov chain model for Japanese kanji-kana characters and English alphabets, assuming that Markov probability of a correct chain of syllables or kanji-kana characters is greater than that of erroneous chains.
tech,40-2-C94-1030,ak
paper proposes new methods using
<term>
m-th order Markov chain model
</term>
for
<term>
Japanese kanji-kana characters
#26566In order to judge three types of the errors, which are characters wrongly substituted, deleted or inserted in a Japanese bunsetsu and an English word, and to correct these errors, this paper proposes new methods using m-th order Markov chain model for Japanese kanji-kana characters and English alphabets, assuming that Markov probability of a correct chain of syllables or kanji-kana characters is greater than that of erroneous chains.
other,46-2-C94-1030,ak
order Markov chain model
</term>
for
<term>
Japanese kanji-kana characters
</term>
and
<term>
English alphabets
</term>
#26572In order to judge three types of the errors, which are characters wrongly substituted, deleted or inserted in a Japanese bunsetsu and an English word, and to correct these errors, this paper proposes new methods using m-th order Markov chain model for Japanese kanji-kana characters and English alphabets, assuming that Markov probability of a correct chain of syllables or kanji-kana characters is greater than that of erroneous chains.
other,50-2-C94-1030,ak
Japanese kanji-kana characters
</term>
and
<term>
English alphabets
</term>
, assuming that
<term>
Markov probability
#26576In order to judge three types of the errors, which are characters wrongly substituted, deleted or inserted in a Japanese bunsetsu and an English word, and to correct these errors, this paper proposes new methods using m-th order Markov chain model for Japanese kanji-kana characters and English alphabets, assuming that Markov probability of a correct chain of syllables or kanji-kana characters is greater than that of erroneous chains.
measure(ment),55-2-C94-1030,ak
English alphabets
</term>
, assuming that
<term>
Markov probability
</term>
of a correct chain of
<term>
syllables
#26581In order to judge three types of the errors, which are characters wrongly substituted, deleted or inserted in a Japanese bunsetsu and an English word, and to correct these errors, this paper proposes new methods using m-th order Markov chain model for Japanese kanji-kana characters and English alphabets, assuming that Markov probability of a correct chain of syllables or kanji-kana characters is greater than that of erroneous chains.
other,62-2-C94-1030,ak
probability
</term>
of a correct chain of
<term>
syllables
</term>
or
<term>
kanji-kana characters
</term>
#26588In order to judge three types of the errors, which are characters wrongly substituted, deleted or inserted in a Japanese bunsetsu and an English word, and to correct these errors, this paper proposes new methods using m-th order Markov chain model for Japanese kanji-kana characters and English alphabets, assuming that Markov probability of a correct chain of syllables or kanji-kana characters is greater than that of erroneous chains.
other,64-2-C94-1030,ak
chain of
<term>
syllables
</term>
or
<term>
kanji-kana characters
</term>
is greater than that of erroneous
#26590In order to judge three types of the errors, which are characters wrongly substituted, deleted or inserted in a Japanese bunsetsu and an English word, and to correct these errors, this paper proposes new methods using m-th order Markov chain model for Japanese kanji-kana characters and English alphabets, assuming that Markov probability of a correct chain of syllables or kanji-kana characters is greater than that of erroneous chains.
other,24-3-C94-1030,ak
well as correcting these errors in
<term>
Japanese bunsetsu
</term>
and
<term>
English words
</term>
. This
#26624From the results of the experiments, it is concluded that the methods is useful for detecting as well as correcting these errors in Japanese bunsetsu and English words.
other,27-3-C94-1030,ak
<term>
Japanese bunsetsu
</term>
and
<term>
English words
</term>
. This paper describes the enhancements
#26627From the results of the experiments, it is concluded that the methods is useful for detecting as well as correcting these errors in Japanese bunsetsu and English words.