[ Performance and Memory Analysis for Large Dataset ] very slow for large numbers of Hits

I am trying to run language on using this scrit

            final LanguageDetector detector = LanguageDetectorBuilder.fromLanguages(ENGLISH, FRENCH, GERMAN, SPANISH, JAPANESE, CHINESE,ITALIAN, PORTUGUESE,ARABIC,RUSSIAN,DUTCH,KOREAN,SWEDISH,HINDI,POLISH).build();

	    long start=System.currentTimeMillis();  


	    final Language detectedLanguage = detector.detectLanguageOf("Zum Vergleich kann es auch nützlich sein, diese Rankings neben einigen etwas älteren Forschungsergebnissen zu sehen. Im Jahr 2013, Common Sense Advisory zur Verfügung gestellt , eine empirische Studie basiert auf einer Wallet World Online (WOW) - definiert als ‚die gesamte wirtschaftliche Chance, sowohl online als auch offline, berechnet durch einen Anteil eines Landes BIP zu allen wichtigen Blöcken dieser Gesellschaft assoziieren. ' Hier ist, was uns ihre Studie gezeigt hat.");
//	    System.out.println(detectedLanguage.toString());
	    long end=System.currentTimeMillis();  
	    System.out.println("Time: "+ (end - start));

it’s taking 700millisecong. which is very slow. which can not be used for 10000+ files… is there any approach to get results with 1-10milliseconds?

or any function like isEnglish(). which will be true only for English…

[the-black-knight-01]

thanks, it got reduced from 600 milliseconds to 70 milliseconds

[Marcono1234]

If I recall correctly the Korean, Chinese and Japanese language models are quite large. So if you know beforehand, that your input is in neither of those languages you can save quite a lot of memory by excluding them.

or any function like isEnglish(). which will be true only for English…

On the other hand, if your input text is in a language which you have not included, or which Lingua does not support, and which is similar to English, Lingua could erroneously claim that the text is in English.