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src: improve algorithm for confidence computation.

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Additionally to the "frequent characters" concept, we add 2
sub-categories, which are the "very frequent characters" and "rare
characters". The former are usually just a few characters which are used
most of the time (like 3 or 4 characters used 40% of the time!), whereas
the later are often a dozen or more characters which are barely used a
few percents of the time, all together.

We use this additional concept to help distinguish very similar
languages, or languages whose frequent characters are a subset of
the ones from another language (typically English, whose alphabet is a
subset of many other European languages).

The mTypicalPositiveRatio is getting rid of, as it was anyway barely of
any use (it was 0.99-something for nearly all languages!). Instead we
get these 2 new ratios: veryFreqRatio and lowFreqRatio, and of course
the associated order counts to know which character are in these sets.
This commit is contained in:
Jehan 2022-12-14 20:02:59 +01:00
parent 4f35cd4416
commit 401eb55dfc
2 changed files with 31 additions and 5 deletions
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19
src/nsLanguageDetector.cpp
View File

@ -37,6 +37,7 @@
*
* ***** END LICENSE BLOCK ***** */
#include <math.h>
#include "nsLanguageDetector.h"
nsDetectState nsLanguageDetector::HandleData(const int* codePoints, PRUint32 cpLen)
@ -164,6 +165,11 @@ nsDetectState nsLanguageDetector::HandleData(const int* codePoints, PRUint32 cpL
/* Adding a non frequent sequence. */
mTotalSeqs++;
}
if (order < mModel->veryFreqCharCount)
mVeryFreqChar++;
if (order > mModel->lowFreqOrder)
mLowFreqChar++;
}
mLastOrder = order;
}
@ -192,8 +198,10 @@ void nsLanguageDetector::Reset(void)
//mCtrlChar = 0;
//mEmoticons = 0;
//mVariousBetween = 0;
mFreqChar = 0;
mOutChar = 0;
mFreqChar = 0;
mVeryFreqChar = 0;
mLowFreqChar = 0;
mOutChar = 0;
}
#include <cstdio>
@ -212,7 +220,7 @@ float nsLanguageDetector::GetConfidence(void)
//float neutralSeqs = mSeqCounters[LANG_NEUTRAL_CAT];
float negativeSeqs = mSeqCounters[LANG_NEGATIVE_CAT];
r = (positiveSeqs + probableSeqs / 4 - negativeSeqs * 4) / mTotalSeqs / mModel->mTypicalPositiveRatio;
r = (positiveSeqs + probableSeqs / 4 - negativeSeqs * 4) / mTotalSeqs;
/* The more characters outside the expected characters
* (proportionnaly to the size of the text), the less confident we
* become in the current language.
@ -222,6 +230,11 @@ float nsLanguageDetector::GetConfidence(void)
r = r * (mTotalChar - mOutChar) / mTotalChar;
r = r * mFreqChar / (mFreqChar + mOutChar);
/* How similar are the very frequent character ratio. */
r = r * (1.0 - fabs((float) mVeryFreqChar / mFreqChar - mModel->veryFreqRatio) / 4.0);
/* How similar are the very rare character ratio. */
r = r * (1.0 - fabs((float) mLowFreqChar / mFreqChar - mModel->lowFreqRatio) / 4.0);
return r;
}
return (float)0.01;

17
src/nsLanguageDetector.h
View File

@ -67,8 +67,17 @@ typedef struct
* characters. Yet it maps to this range of orders.
*/
int freqCharCount;
float mTypicalPositiveRatio;
/* Most languages have 3 or 4 characters which are used more than 40% of the
* times. We count how many they are and what ratio they are used.
*/
int veryFreqCharCount;
float veryFreqRatio;
/* Most languages will have a whole range of characters which in cumulated
* total are barely used a few percents of the times. We count how many they
* are and what ratio they are used.
*/
int lowFreqOrder;
float lowFreqRatio;
} LanguageModel;
typedef enum {
@ -105,6 +114,10 @@ protected:
/*PRUint32 mVariousBetween;*/
/* Characters that fall in our sampling range */
PRUint32 mFreqChar;
/* Most common characters from our sampling range */
PRUint32 mVeryFreqChar;
/* Most rare characters from our sampling range */
PRUint32 mLowFreqChar;
PRUint32 mOutChar;
private: