Abstract: Provided are sustained-release pharmaceutical compositions including a ketamine pamoate salt and a pharmaceutically acceptable carrier thereof. The compositions include aqueous suspension, solution and matrix delivery system, which can provide sustained release for anesthesia, analgesia or treatment of central nervous system and anti-inflammatory diseases.

Abstract: A foreign language writing service method includes: recognizing, when a mixed text of foreign language portions and mother tongue portions is entered by a learner, the mother tongue portions from the mixed text; translating the mother tongue portions; combining a mother tongue translation result with the foreign language portions of the mixed text to generate a combined text; and providing the learner with the combined text of the mother tongue translation result and the foreign language portions of the mixed text.

Abstract: A method for automatically detecting errors in machine translation using a parallel corpus includes analyzing morphemes of a target language sentence in the parallel corpus and a machine-translated target language sentence, corresponding to a source language sentence, to classify the morphemes into words; aligning by words and decoding, respectively, a group of the source language sentence and the machine-translated target language sentence, and a group of the source language sentence and the target language sentence in the parallel corpus; classifying by types errors in the machine-translated target language sentence by making a comparison, word by word, between the decoded target language sentence in the parallel corpus and the decoded machine-translated target language sentence; and computing error information in the machine-translated target language sentence by examining a frequency of occurrence of the classified error types.

Abstract: A post-editing apparatus for correcting translation errors, includes: a translation error search unit for estimating translation errors using an error-specific language model suitable for a type of error desired to be estimated from translation result obtained using a translation system, and determining an order of correction of the translation errors; and a corrected word candidate generator for sequentially generating error-corrected word candidates for respective estimated translation errors on a basis of analysis of an original text of the translation system. The post-editing apparatus further includes a corrected word selector for selecting a final corrected word from among the error-corrected word candidates by using the error-specific language model suitable for the type of error desired to be corrected, and incorporating the final corrected word in the translation result, thus correcting the translation errors.

Abstract: A hybrid translation apparatus includes a source language input unit for generalizing an input source language sentence for each node; a statistics-based translation knowledge database(DB) for storing learning data generalized for each node to be acquired; a first translation result generating unit for transforming the source language sentence generalized for each node into a node expression using the statistics-based translation knowledge to generate a first translation result; and a second translation result generating unit for repeatedly performing the generation of a target word for each node on the first translation result using pattern-based knowledge to generate a second translation result as target words for the respective nodes.

Abstract: The present invention provides a Korean-English hybrid automatic translation method for providing translation from Korean to English, includes: performing a morpheme analysis and a syntactic analysis on a Korean input source text; segmenting the Korean input source text into at least two source text segments, based on the results of the morpheme analysis and the syntactic analysis; and generating a PBMT (pattern-based machine translation) translated text segment and a SMT (statistical machine translation) translated text segment with respect to each of the source text segments. Further, the method includes determining, as final translation result, one of the PBMT translated text segment and the SMT translated text segment with respect to each source text segment, based on predetermined weight information; and composing the translated text segments with respect to the source text segments of the Korean input source text into one English translated text by using the determined final translation results.

Abstract: A machine-translation apparatus using multi-level verbal-phrase patterns includes: a simple sentence generation unit for generating an input simple sentence; a basic verbal-phrase pattern-matching unit for trying a match of a semantic code of each case component of the input simple sentence with basic verbal-phrase patterns; a default verbal-phrase pattern matching unit for trying a match of a size and case prepositions of the input simple sentence with default verbal-phrase patterns having a verb identical to that of the input simple sentence; a default word-order matching unit for trying a match of a word-order of the input simple sentence with default word-order verbal-phrase patterns having a case component structure identical to that of the input simple sentence; and a default preposition matching unit for generating a target sentence of an input sentence with default preposition patterns having a context identical to that of the input simple sentence.

Abstract: A translation-memory application method for automatic translation includes: generating TM-expanded forms by applying TM expansion rules respectively to source sentences whose morphemes have been analyzed; storing in an expanded TM database translated sentences corresponding to the generated TM-expanded source sentences; analyzing morphemes if an input sentence does not match any of the source sentences stored in basic TM database; generating a TM-expanded form by applying pertinent ones among the TM expansion rules to the input sentence whose morphemes have been analyzed; and producing, if the TM-expanded input sentence matches one of the TM-expanded source sentences stored in the expanded TM database, a translated output corresponding to the matched TM-expanded source sentence.

Abstract: A foreign language writing service method includes: recognizing, when a mixed text of foreign language portions and mother tongue portions is entered by a learner, the mother tongue portions from the mixed text; translating the mother tongue portions; combining a mother tongue translation result with the foreign language portions of the mixed text to generate a combined text; and providing the learner with the combined text of the mother tongue translation result and the foreign language portions of the mixed text.

Abstract: A hybrid translation apparatus includes a source language input unit for generalizing an input source language sentence for each node; a statistics-based translation knowledge database(DB) for storing learning data generalized for each node to be acquired; a first translation result generating unit for transforming the source language sentence generalized for each node into a node expression using the statistics-based translation knowledge to generate a first translation result; and a second translation result generating unit for repeatedly performing the generation of a target word for each node on the first translation result using pattern-based knowledge to generate a second translation result as target words for the respective nodes.

Abstract: A post-editing apparatus for correcting translation errors, includes: a translation error search unit for estimating translation errors using an error-specific language model suitable for a type of error desired to be estimated from translation result obtained using a translation system, and determining an order of correction of the translation errors; and a corrected word candidate generator for sequentially generating error-corrected word candidates for respective estimated translation errors on a basis of analysis of an original text of the translation system. The post-editing apparatus further includes a corrected word selector for selecting a final corrected word from among the error-corrected word candidates by using the error-specific language model suitable for the type of error desired to be corrected, and incorporating the final corrected word in the translation result, thus correcting the translation errors.

Abstract: A translation-memory application method for automatic translation includes: generating TM-expanded forms by applying TM expansion rules respectively to source sentences whose morphemes have been analyzed; storing in an expanded TM database translated sentences corresponding to the generated TM-expanded source sentences; analyzing morphemes if an input sentence does not match any of the source sentences stored in basic TM database; generating a TM-expanded form by applying pertinent ones among the TM expansion rules to the input sentence whose morphemes have been analyzed; and producing, if the TM-expanded input sentence matches one of the TM-expanded source sentences stored in the expanded TM database, a translated output corresponding to the matched TM-expanded source sentence.

Abstract: A document translation apparatus includes a document processing module for analyzing associative relations between nouns or noun phrases within an input document to be translated to generate analysis information on texts; and a document translation module for selecting target words for the respective texts in reference to the text analysis information to generate morphemes corresponding to the target words, thereby producing a translated document corresponding to the input document.

Abstract: A method for automatically detecting errors in machine translation using a parallel corpus includes analyzing morphemes of a target language sentence in the parallel corpus and a machine-translated target language sentence, corresponding to a source language sentence, to classify the morphemes into words; aligning by words and decoding, respectively, a group of the source language sentence and the machine-translated target language sentence, and a group of the source language sentence and the target language sentence in the parallel corpus; classifying by types errors in the machine-translated target language sentence by making a comparison, word by word, between the decoded target language sentence in the parallel corpus and the decoded machine-translated target language sentence; and computing error information in the machine-translated target language sentence by examining a frequency of occurrence of the classified error types.

Abstract: A machine-translation apparatus using multi-level verbal-phrase patterns includes: a simple sentence generation unit for generating an input simple sentence; a basic verbal-phrase pattern-matching unit for trying a match of a semantic code of each case component of the input simple sentence with basic verbal-phrase patterns; a default verbal-phrase pattern matching unit for trying a match of a size and case prepositions of the input simple sentence with default verbal-phrase patterns having a verb identical to that of the input simple sentence; a default word-order matching unit for trying a match of a word-order of the input simple sentence with default word-order verbal-phrase patterns having a case component structure identical to that of the input simple sentence; and a default preposition matching unit for generating a target sentence of an input sentence with default preposition patterns having a context identical to that of the input simple sentence.

Abstract: The present invention provides a Korean-English hybrid automatic translation method for providing translation from Korean to English, includes: performing a morpheme analysis and a syntactic analysis on a Korean input source text; segmenting the Korean input source text into at least two source text segments, based on the results of the morpheme analysis and the syntactic analysis; and generating a PBMT (pattern-based machine translation) translated text segment and a SMT (statistical machine translation) translated text segment with respect to each of the source text segments. Further, the method includes determining, as final translation result, one of the PBMT translated text segment and the SMT translated text segment with respect to each source text segment, based on predetermined weight information; and composing the translated text segments with respect to the source text segments of the Korean input source text into one English translated text by using the determined final translation results.