1. An automated method for debugging training data used to train an automated language identifier, said method comprising: (a) collecting a text written in a predetermined language; (b) generating an occurrence count for each of a plurality of words, by counting the number of times each of said words is found within the text; (c) generating an occurrence ratio (OR) of each of said words by dividing the occurrence count by substantially the total number of words in each text; (d) repeating said (a), (b), and (c) to generate ORs for a plurality of texts; and (e) filtering, by a computer, words from one of said texts which have an occurrence ratio that is substantially distinct from corresponding occurrence ratios of an other of said texts, to generate a clean text.
1. An automated method for debugging training data used to train an automated language identifier, said method comprising: (a) collecting a text written in a predetermined language; (b) generating an occurrence count for each of a plurality of words, by counting the number of times each of said words is found within the text; (c) generating an occurrence ratio (OR) of each of said words by dividing the occurrence count by substantially the total number of words in each text; (d) repeating said (a), (b), and (c) to generate ORs for a plurality of texts; and (e) filtering, by a computer, words from one of said texts which have an occurrence ratio that is substantially distinct from corresponding occurrence ratios of an other of said texts, to generate a clean text. 10. The method of claim 1 , wherein the occurrence ratio (OR) is determined by the following: 
 Occurrence ratio=occurrence count of a word/total sum of occurrence counts of all word entries in a hash table.