Negative filter
Japanese, bunsetsu 15
(480.2 per million)
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.
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,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,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,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,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.
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 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,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.
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,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,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.
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.
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,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.
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.