Abstract: A statistical translation memory (TMEM) may be generated by training a translation model with a naturally generated TMEM. A number of tuples may be extracted from each translation pair in the TMEM. The tuples may include a phrase in a source language and a corresponding phrase in a target language. The tuples may also include probability information relating to the phrases generated by the translation model.

Abstract: A machine translation system may use non-parallel monolingual corpora to generate a translation lexicon. The system may identify identically spelled words in the two corporal and use them as a seed lexicon. The system may use various clues 1 e.g., context and frequency, to identify and score other possible translation pairs 1 using the seed lexicon as a basis. An alternative system may use a small bilingual lexicon in addition to non-parallel corpora to learn translations of unknown words and to generate a parallel corpus.

Abstract: Compounds of formula (I) or a pharmaceutically acceptable salt, solvate or prodrug thereof, are disclosed: wherein R1 is C1-6alkyl, haloC1-6alkyl, C2-6alkenyl, amino, monoC1-4alkylamino or diC1-4alkylamino; R2 and R3, which may be the same or different, are hydrogen, halogen, C1-6alkyl, haloC1-6alkyl, C1-4alkoxy, haloC1-4alkoxy, cyano, amino, monoC1-4alkylamino or diC1-4alkylamino; each R4, which may be the same or different, is C1-6alkyl, halogen, C1-6alkyl, haloC1-6alkyl, C1-4alkoxy, haloC1-4alkoxy, cyano, nitro, amino, monoC1-4alkylamino or diC1-4alkylamino; p is 0, 1 or 2; n is 1 or 2; R5 and R6, which may be the same or different, are hydrogen, halogen, C1-6alkyl, haloC1-6alkyl, C1-4alkoxy, haloC1-4alkoxy, cyano, amino, monoC1-4alkylamino or diC1-4alkylamino; and Het is thienyl, pyridyl, pyrimidinyl, pyridazinyl, pyrimidinyl, pyrazinyl, imidazolyl, pyrazolyl, pyrrolyl, quinolyl, thiazolyl or furyl, each of which may be substituted by one or more groups independently selected from the list consisting

Abstract: A machine translation system may use non-parallel monolingual corpora to generate a translation lexicon. The system may identify identically spelled words in the two corpora, and use them as a seed lexicon. The system may use various clues, e.g., context and frequency, to identify and score other possible translation pairs, using the seed lexicon as a basis. An alternative system may use a small bilingual lexicon in addition to non-parallel corpora to learn translations of unknown words and to generate a parallel corpus.

Abstract: The present invention relates to compounds of formula (I), or salts or solvates thereof, their use in the manufacture of medicaments for treating neurological and neuropsychiatric disorders, in particular psychoses, dementia or attention deficit disorder. The invention further comprises processes to make these compounds and pharmaceutical formulations thereof.

Abstract: Compounds of formula (I) or a pharmaceutically acceptable salt, solvate or prodrug thereof, are disclosed: wherein R1 is C1-6alkyl, haloC1-6alkyl, C2-6alkenyl, amino, monoC1-4alkylamino or diC1-4alkylamino; R2 and R3, which may be the same or different, are hydrogen, halogen, C1-6alkyl, haloC1-6alkyl, C1-4alkoxy, haloC1-4alkoxy, cyano, amino, monoC1-4alkylamino or diC1-4alkylamino; each R4, which may be the same or different, is C1-6alkyl, halogen, C1-6alkyl, haloC1-6alkyl, C1-4alkoxy, haloC1-4alkoxy, cyano, nitro, amino, monoC1-4alkylamino or diC1-4alkylamino; p is 0, 1 or 2; n is 1 or 2; R5 and R6, which may be the same or different, are hydrogen, halogen, C1-6alkyl, haloC1-6alkyl, C1-4alkoxy, haloC1-4alkoxy, cyano, amino, monoC1-4alkylamino or diC1-4alkylamino; and Het is thienyl, pyridyl, pyrimidinyl, pyridazinyl, pyrimidinyl, pyrazinyl, imidazolyl, pyrazolyl, pyrrolyl, quinolyl, thiazolyl or furyl, each of which may be substituted by one or more groups independently selected from the list consisting

Abstract: Machine translation decoding is accomplished by receiving as input a text segment in a source language to be translated into a target language, generating an initial translation as a current target language translation, applying one or more modification operators to the current target language translation to generate one or more modified target language translations, determining whether one or more of the modified target language translations represents an improved translation in comparison with the current target language translation, setting a modified target language translation as the current target language translation, and repeating these steps until occurrence of a termination condition. Automatically generating a tree (e.g., either a syntactic tree or a discourse tree) can be accomplished by receiving as input a tree corresponding to a source language text segment, and applying one or more decision rules to the received input to generate a tree corresponding to a target language text segment.

Abstract: The present invention relates to compounds of formula (I), or to salts or solvates thereof, their use in the manufacture of medicaments for treating neurological and neuropsychiatric disorders, in particular psychoses, dementia or attention deficit disorder. The invention further comprises processes to make these compounds and pharmaceutical formulations thereof.

Abstract: A machine translation (MT) system may utilize a phrase-based joint probability model. The model may be used to generate source and target language sentences simultaneously. In an embodiment, the model may learn phrase-to-phrase alignments from word-to-word alignments generated by a word-to-word statistical MT system. The system may utilize the joint probability model for both source-to-target and target-to-source translation applications.

Abstract: The invention provides a compound of formula (I) or a salt or solvate thereof: wherein R1, n, X, Y and Z are as defined in the specification, and uses of such compounds. The compounds inhibit GlyT1 transporters and are useful in the treatment of certain neurological and neuropsychiatric disorders, including schizophrenia.

Abstract: Embodiments of the present invention provide a system and method for providing a translation service. The method comprises providing a translation interface accessible via a network. The translation interface receives specialized data associated with a domain from a member. A text string written in a source language is received from the member via the translation interface. A domain-based translation engine is selected. The domain-based translation engine may be associated with a source language, a target language, and a domain. The text string is translated into the target language using, at least in part, by the selected domain-based translation engine. The translated text string is transmitted to the member via the Internet. In some embodiments, a translation memory is generated based on the specialized data.

Abstract: Compounds of formula (I) or a pharmaceutically acceptable salt, solvate or prodrug thereof, are disclosed: wherein R1 is C1-6alkyl, haloC1-6alkyl, C2-6alkenyl, amino, monoC1-4alkylamino or diC1-4alkylamino; R2 and R3, which may be the same or different, are hydrogen, halogen, C1-6alkyl, haloC1-6alkyl, C1-4alkoxy, haloC1-4alkoxy, cyano, amino, monoC1-4alkylamino or diC1-4alkylamino; each R4, which may be the same or different, is C1-6alkyl, halogen, C1-6alkyl, haloC1-6alkyl, C1-4alkoxy, haloC1-4alkoxy, cyano, nitro, amino, monoC1-4alkylamino or diC1-4alkylamino; p is 0, 1 or 2; n is 1 or 2; R5 and R6, which may be the same or different, are hydrogen, halogen, C1-6alkyl, haloC1-6alkyl, C1-4alkoxy, haloC1-4alkoxy, cyano, amino, monoC1-4alkylamino or diC1-4alkylamino; and Het is thienyl, pyridyl, pyrimidinyl, pyridazinyl, pyrimidinyl, pyrazinyl, imidazolyl, pyrazolyl, pyrrolyl, quinolyl, thiazolyl or furyl, each of which may be substituted by one or more groups independently selected from the list consisting

Abstract: Parallelization of word alignment for a text-to-text operation. The training data is divided into multiple groups, and training is carried out of each group on separate processors. Different techniques can be carried out to increase the speed of the processing. The hookups can be done only once for all of multiple different iterations. Moreover, parallel operations can apply only to the counts, since this may be the most time-consuming part.

Abstract: A system and method for aligning words in parallel segments is provided. A first probability distribution of word alignments within a first corpus comprising unaligned word-level parallel segments according to a model estimate is calculated. The model estimate is modified according to the first probability distribution. One or more sub-models associated with the modified model estimate are discriminatively re-ranked according to word-level annotated parallel segments. A second probability distribution of the word alignments within the first corpus is calculated according to the re-ranked sub-models associated with the modified model estimate.

Abstract: A statistical machine translation (MT) system may use a large monolingual corpus to improve the accuracy of translated phrases/sentences. The MT system may produce a alternative translations and use the large monolingual corpus to (re)rank the alternative translations.

Abstract: A statistical machine translation (MT) system may include a translation memory (TMEM) and a decoder. The decoder may translate an input text segment using a statistical MT decoding algorithm, for example, a greedy decoding algorithm. The system may generate a cover of the input text segment from text segments in the TMEM. The decoder may use the cover as an initial translation in the decoding operation.

Abstract: Systems, computer programs, and methods for identifying parallel documents and/or fragments in a bilingual collection are provided. The method for identifying parallel sub-sentential fragments in a bilingual collection comprises translating a source document from a bilingual collection. The method further includes querying a target library associated with the bilingual collection using the translated source document, and identifying one or more target documents based on the query. Subsequently, a source sentence associated with the source document is aligned to one or more target sentences associated with the one or more target documents. Finally, the method includes determining whether a source fragment associated with the source sentence comprises a parallel translation of a target fragment associated with the one or more target sentences.

Abstract: A learning system for a text-to-text application such as a machine translation system. The system has questions, and a matrix of correct answers to those questions. Any of the many different correct answers within the matrix can be considered as perfectly correct answers to the question. The system operates by displaying a question, which may be a phrase to be translated, and obtaining an answer to the question from the user. The answer is compared against the matrix and scored. Feedback may also be provided to the user.

Abstract: To automatically annotate an essay, a sentence of the essay is identified and a feature associated with the sentence is determined. In addition, a probability of the sentence being a discourse element is determined by mapping the feature to a model. The model having been generated by a machine learning application based on at least one annotated essay. Furthermore, the essay is annotated based on the probability.

Abstract: A training system for text to text application. The training system finds groups of documents, and identifies automatically similar documents in the groups which are similar. The automatically identified documents can then be used for training of the text to text application. The comparison uses reduced size versions of the documents in order to minimize the amount of processing.