Provided are techniques for generating and customizing summarized notes. A template is selected from a plurality of templates based on a context using a machine learning model. The template includes one or more translatable string resources with variables to represent key attributes extracted from historical notes. A summarized note is generated using values of the key attributes for the variables in the translatable string resources of the template.

An automatic scroll control method for synchronizing positions of an original text and a translation includes displaying, by a processor of a terminal device, the original text on a first display and displaying the translation corresponding to the original text on a second display; and when the original text or the translation is scrolled by a drag operation of a user, synchronizing the display positions of the original text and the translation with each other.

An automatic scroll control method for synchronizing positions of an original text and a translation includes displaying, by a processor of a terminal device, the original text on a first display and displaying the translation corresponding to the original text on a second display; and when the original text or the translation is scrolled by a drag operation of a user, synchronizing the display positions of the original text and the translation with each other.

There is provided a method of speech-to-speech translation including receiving at a mobile device input speech data associated with speech in a first language and converting the input speech data into input text data using a speech-to-text conversion engine (STT engine) onboard the mobile device. The method also includes translating the input text data to form a translated text data using a text-to-text translation engine (TTT engine) onboard the mobile device. The translated text data is associated with a second language. In addition, the method includes converting the translated text data into output speech data using a text-to-speech conversion engine (TTS engine) onboard the mobile device, and outputting at the mobile device a device output based on the output speech data. Mobile devices and computer-readable storage media for speech-to-speech translation are also provided.

There is provided a method of speech-to-speech translation including receiving at a mobile device input speech data associated with speech in a first language and converting the input speech data into input text data using a speech-to-text conversion engine (STT engine) onboard the mobile device. The method also includes translating the input text data to form a translated text data using a text-to-text translation engine (TTT engine) onboard the mobile device. The translated text data is associated with a second language. In addition, the method includes converting the translated text data into output speech data using a text-to-speech conversion engine (TTS engine) onboard the mobile device, and outputting at the mobile device a device output based on the output speech data. Mobile devices and computer-readable storage media for speech-to-speech translation are also provided.

An approach for generating synthetic treebanks to be used in training a parser in a production system is provided. A processor receives a request to generate one or more synthetic treebanks from a production system, wherein the request indicates a language for the one or more synthetic treebanks. A processor retrieves at least one corpus of text in which the requested language is present. A processor provides the at least one corpus to a transformer enhanced parser neural network model. A processor generates at least one synthetic treebank associated with a string of text from the at least one corpus of text in which the requested language is present. A processor sends the at least one synthetic treebank to the production system, wherein the production system trains a parser utilized by the production system with the at least one synthetic treebank.

An approach for generating synthetic treebanks to be used in training a parser in a production system is provided. A processor receives a request to generate one or more synthetic treebanks from a production system, wherein the request indicates a language for the one or more synthetic treebanks. A processor retrieves at least one corpus of text in which the requested language is present. A processor provides the at least one corpus to a transformer enhanced parser neural network model. A processor generates at least one synthetic treebank associated with a string of text from the at least one corpus of text in which the requested language is present. A processor sends the at least one synthetic treebank to the production system, wherein the production system trains a parser utilized by the production system with the at least one synthetic treebank.

In an implementation, a method for detecting anomalies in textual items is provided. The method includes: receiving a first plurality of textual items by a computing device; training a language model using the received first plurality of textual items by the computing device; after training the language model, receiving a second plurality of textual items by the computing device; calculating a cross-entropy for each textual item in the second plurality of textual items by the computing device using the language model; and detecting an anomaly in at least one of the textual items of the second plurality of textual items by the computing device using the calculated cross-entropies.

In an implementation, a method for detecting anomalies in textual items is provided. The method includes: receiving a first plurality of textual items by a computing device; training a language model using the received first plurality of textual items by the computing device; after training the language model, receiving a second plurality of textual items by the computing device; calculating a cross-entropy for each textual item in the second plurality of textual items by the computing device using the language model; and detecting an anomaly in at least one of the textual items of the second plurality of textual items by the computing device using the calculated cross-entropies.

A document translation method includes: displaying a source text display region, a translated text region, and an editing region, wherein textual content in a document to be translated is displayed in the source text display region, and reference translated text for the textual content is displayed in the translated text region; and providing a translated text recommendation from the reference translated text according to input from a user within the editing region. The method further includes: displaying the translation recommendation in the editing area as a translation result, if a confirmation operation for the translation recommendation is detected; and receiving a translation inputted by the user that is different from the translation recommendation and displaying the translation inputted by the user in the editing area as the translation result, if a non-confirmation operation for the translation recommendation is detected.