#26551In order to judge three types of the errors, which are characters wrongly substituted, deleted or inserted in a Japanese bunsetsu and anEnglish 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 andEnglish alphabets, assuming that Markov probability of a correct chain of syllables or kanji-kana characters is greater than that of erroneous chains.
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 anatural language, it has been difficult to detect error characters which are wrongly deleted and inserted.
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 theseerrors, 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,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 theerrors, 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,27-3-C94-1030,ak
in
<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 andEnglish words.
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 aJapanese 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,1-1-C94-1030,ak
<term>
language families
</term>
. In
<term>
optical character recognition
</term>
and
<term>
continuous speech recognition
#26499Inoptical 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,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 forJapanese 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 inJapanese bunsetsu and English words.
tech,40-2-C94-1030,ak
this 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 usingm-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
correct 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 orkanji-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 thatMarkov probability of a correct chain of syllables or kanji-kana characters is greater than that of erroneous chains.
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 andcontinuous speech recognition of a natural language, it has been difficult to detect error characters which are wrongly deleted and inserted.
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 ofsyllables or kanji-kana characters is greater than that of erroneous chains.
other,19-1-C94-1030,ak
</term>
, 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 detecterror characters which are wrongly deleted and inserted.
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 arecharacters 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.