Abstract: A translation system receives examples of translations between a first language and a second language. In response to receiving request to translate a source text from the first language to the second language, the system ranks the examples based on the example's applicability to one or more portions of the source text. The system performs additional training of a neural network that was pre-trained to translate from the first language to the second language, where the additional training is based on one or more top-ranking examples. The system translates the source text to the second language using the additionally trained neural network.

Abstract: Techniques for the generation of dubbed audio for an audio/video are described.

Abstract: Techniques for neural machine translation with a controlled output are described. An exemplary method includes receiving a request to perform a machine language translation of text using a translation model; determining a desired target length of the text; using the translation model to translate the text, the identified translation model including an encoder and decoder portion, the decoder portion in accept as an input into a decoder stack at least an embedding of a token of the text, a position of the token within the text, and an indication of length; and output a result of the machine language translation to a requester.

Abstract: System and method for providing a computer-assisted translation from a source language to a target language, using a generic NMT model and a translation memory. An input text segment is received, and input context information is received. The input context information is indicative of circumstances in which the input text segment is used, the input text segment being in the source language. An estimated translation of the input text segment into the target language is calculated, using a generic neural machine translation “NMT” model for providing a generalised machine translation from the source language to the target language, and a translation memory comprising translation elements; each translation element comprising a source language text segment, a corresponding target language text segment. The estimated translation is provided to a user, for correction by the user.

Abstract: System and method for providing a computer-assisted translation from a source language to a target language, using a generic NMT model and a translation memory. An input text segment is received, and input context information is received. The input context information is indicative of circumstances in which the input text segment is used, the input text segment being in the source language. An estimated translation of the input text segment into the target language is calculated, using a generic neural machine translation “NMT” model for providing a generalised machine translation from the source language to the target language, and a translation memory comprising translation elements; each translation element comprising a source language text segment, a corresponding target language text segment. The estimated translation is provided to a user, for correction by the user.

Abstract: A system for recognizing continuous speech, for example for automatic dictation applications, uses a bigramme language model organized as a network with finite probability states. The system also uses methods of estimating the probabilities associated with the bigrammes and of representing the model of the language in a tree-like probability network.