Machine Zone Inc.

Mz IP Holdings, LLC

Pidong Wang

Nikhil Bojja

Shiman Guo

Fredrik Erik Linder

Bartlomiej Puzon

Shivasankari Kannan

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving a plurality of word strings in a first language, each received word string comprising a plurality of words, identifying one or more named entities in each received word string using a statistical classifier that was trained using training data comprising a plurality of features, wherein one of the features is a word shape feature that comprises a respective token for each letter of a respective word wherein each token signifies a case of the letter or whether the letter is a digit, and translating the received word strings from the first language to a second language including preserving the respective identified named entities in each received word string during translation.

Named entity recognition on chat data

Implementations of the present disclosure are directed to a method, a system, and an article for translating chat messages. An example method can include: receiving an electronic text message from a client device of a user; normalizing the electronic text message to generate a normalized text message; tagging at least one phrase in the normalized text message with a marker to generate a tagged text message, the marker indicating that the at least one phrase will be translated using a rule-based system; translating the tagged text message using the rule-based system and a machine translation system to generate an initial translation; and post-processing the initial translation to generate a final translation.

System and method for translating chat messages

Implementations of the present disclosure are directed to a method, a system, and a computer program storage device for identifying a language in a message. Non-language characters are removed from a text message to generate a sanitized text message. An alphabet and/or a script are detected in the sanitized text message by performing at least one of (i) an alphabet-based language detection test to determine a first set of scores and (ii) a script-based language detection test to determine a second set of scores. Each score in the first set of scores represents a likelihood that the sanitized text message includes the alphabet for one of a plurality of different languages. Each score in the second set of scores represents a likelihood that the sanitized text message includes the script for one of the plurality of different languages. The language in the sanitized text message is identified based on at least one of the first set of scores, the second set of scores, and a combination of the first and second sets of scores.

Systems and methods for language detection

Implementations of the present disclosure are directed to a method, a system, and a computer program storage device for detecting a language in a text message. A plurality of different language detection tests are performed on a message associated with a user. Each language detection test determines a set of scores representing a likelihood that the message is in one of a plurality of different languages. One or more combinations of the score sets are provided as input to one or more distinct classifiers. Output from each of the classifiers includes a respective indication that the message is in one of the different languages. The language in the message may be identified as being the indicated language from one of the classifiers, based on a confidence score and/or an identified linguistic domain.

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Mountain View, CA, United States of America

Pidong Wang