other,8-2-C94-1030,bq |
order to judge three types of the
<term>
|
errors
|
</term>
, which are characters wrongly substituted
|
#20649
In 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,50-2-C94-1030,bq |
Japanese kanji-kana characters
</term>
and
<term>
|
English alphabets
|
</term>
, assuming that
<term>
Markov probability
|
#20691
In 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,55-2-C94-1030,bq |
English alphabets
</term>
, assuming that
<term>
|
Markov probability
|
</term>
of a correct chain of
<term>
syllables
|
#20696
In 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. |
other,24-3-C94-1030,bq |
well as correcting these errors in
<term>
|
Japanese bunsetsu
|
</term>
and
<term>
English words
</term>
. This
|
#20739
From 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. |
other,71-2-C94-1030,bq |
characters
</term>
is greater than that of
<term>
|
erroneous chains
|
</term>
. From the results of the experiments
|
#20712
In 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 oferroneous chains. |
other,27-3-C94-1030,bq |
in
<term>
Japanese bunsetsu
</term>
and
<term>
|
English words
|
</term>
. This paper describes the enhancements
|
#20742
From 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,64-2-C94-1030,bq |
correct chain of
<term>
syllables
</term>
or
<term>
|
kanji-kana characters
|
</term>
is greater than that of
<term>
erroneous
|
#20705
In 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. |
tech,5-1-C94-1030,bq |
optical character recognition
</term>
and
<term>
|
continuous speech recognition
|
</term>
of a
<term>
natural language
</term>
|
#20618
In 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,25-2-C94-1030,bq |
<term>
Japanese bunsetsu
</term>
and an
<term>
|
English word
|
</term>
, and to correct these
<term>
errors
|
#20666
In 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,46-2-C94-1030,bq |
order Markov chain model
</term>
for
<term>
|
Japanese kanji-kana characters
|
</term>
and
<term>
English alphabets
</term>
|
#20687
In 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,19-1-C94-1030,bq |
</term>
, it has been difficult to detect
<term>
|
error characters
|
</term>
which are wrongly deleted and inserted
|
#20632
In 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,32-2-C94-1030,bq |
word
</term>
, and to correct these
<term>
|
errors
|
</term>
, this paper proposes new methods
|
#20673
In 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,40-2-C94-1030,bq |
this paper proposes new methods using
<term>
|
m-th order Markov chain model
|
</term>
for
<term>
Japanese kanji-kana characters
|
#20681
In 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,10-1-C94-1030,bq |
continuous speech recognition
</term>
of a
<term>
|
natural language
|
</term>
, it has been difficult to detect
|
#20623
In optical character recognition and continuous speech recognition of anatural language, it has been difficult to detect error characters which are wrongly deleted and inserted. |
tech,1-1-C94-1030,bq |
<term>
language families
</term>
. In
<term>
|
optical character recognition
|
</term>
and
<term>
continuous speech recognition
|
#20614
Inoptical 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,62-2-C94-1030,bq |
probability
</term>
of a correct chain of
<term>
|
syllables
|
</term>
or
<term>
kanji-kana characters
</term>
|
#20703
In 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,21-2-C94-1030,bq |
substituted , deleted or inserted in a
<term>
|
Japanese bunsetsu
|
</term>
and an
<term>
English word
</term>
,
|
#20662
In 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. |