1. A computer-implemented method of identifying a language in a message, the method comprising: obtaining a text message generated by a user; removing non-language characters from the text message to generate a sanitized text message; detecting an alphabet and a script present in the sanitized text message, wherein (i) detecting the alphabet comprises performing an alphabet-based language detection test to determine a first set of scores, and wherein each score in the first set of scores represents a likelihood that the sanitized text message comprises the alphabet for one of a plurality of different languages, and (ii) detecting the script comprises performing a script-based language detection test to determine a second set of scores, and wherein each score in the second set of scores represents a likelihood that the sanitized text message comprises the script for one of the plurality of different languages; providing one or more combinations of the first and second sets of scores as input to one or more classifiers including a first classifier and a second classifier, wherein the first classifier was trained using outputs from a first combination of language detection tests and the second classifier was trained using outputs from a second combination of language detection tests; obtaining as output from at least one of the one or more classifiers a respective confidence score that the sanitized text message is in one of a plurality of different languages; and identifying the language in the sanitized text message based on the confidence score from at least one of the one or more classifiers.
1. A computer-implemented method of identifying a language in a message, the method comprising: obtaining a text message generated by a user; removing non-language characters from the text message to generate a sanitized text message; detecting an alphabet and a script present in the sanitized text message, wherein (i) detecting the alphabet comprises performing an alphabet-based language detection test to determine a first set of scores, and wherein each score in the first set of scores represents a likelihood that the sanitized text message comprises the alphabet for one of a plurality of different languages, and (ii) detecting the script comprises performing a script-based language detection test to determine a second set of scores, and wherein each score in the second set of scores represents a likelihood that the sanitized text message comprises the script for one of the plurality of different languages; providing one or more combinations of the first and second sets of scores as input to one or more classifiers including a first classifier and a second classifier, wherein the first classifier was trained using outputs from a first combination of language detection tests and the second classifier was trained using outputs from a second combination of language detection tests; obtaining as output from at least one of the one or more classifiers a respective confidence score that the sanitized text message is in one of a plurality of different languages; and identifying the language in the sanitized text message based on the confidence score from at least one of the one or more classifiers. 9. The method of claim 1 , wherein the one or more classifiers comprise at least one of a supervised learning model, a partially supervised learning model, an unsupervised learning model, and an interpolation.