Abstract: A method for improving word alignment quality in a multilingual corpus including a plurality of corresponding sentence pairs between any two languages among a first language, a second language and at least one other language and word alignment information between each of the plurality of corresponding sentence pairs, the method includes inducing word alignment between a first sentence of the first language and a second sentence of the second language by using the word alignment information between the first sentence of the first language and a third sentence of the other language corresponding to the first and second sentences and the word alignment information between the second sentence of the second language and the third sentence of the other language, and combining induced word alignment and the word alignment information between the first sentence of the first language and the second sentence of the second language in the multilingual corpus.

Abstract: A method for improving word alignment quality in a multilingual corpus including a plurality of corresponding sentence pairs between any two languages among a first language, a second language and at least one other language and word alignment information between each of the plurality of corresponding sentence pairs, the method includes inducing word alignment between a first sentence of the first language and a second sentence of the second language by using the word alignment information between the first sentence of the first language and a third sentence of the other language corresponding to the first and second sentences and the word alignment information between the second sentence of the second language and the third sentence of the other language, and combining induced word alignment and the word alignment information between the first sentence of the first language and the second sentence of the second language in the multilingual corpus.

Abstract: A phrase-based statistics machine translation method includes for phrases in an input sentence, performing fuzzy matching in a pre-constructed phrase table. In the method, by performing fuzzy matching on the phrases, high quality translations can be generated for long phrases in the input sentence, thus the quality of the translation can be effectively increased with respect to the machine translation systems based on phrase exactly matching.

Abstract: The method for aligning parallel spoken language corpora comprises obtaining a statistics method and dictionaries-based word alignment set from the parallel spoken language corpora, aligning chunks of the parallel spoken language corpora by using the statistics method and dictionaries-based word alignment set, to obtain a chunk alignment set, and aligning words in aligned chunks of the parallel spoken language corpora to obtain a chunk alignment-based word alignment set. Chunk alignment set and word alignment set are obtained by aligning chunks in parallel spoken language corpora in a corpus repository using a statistics method and dictionaries-based high precision word alignment set obtained from the parallel spoken language corpora and further aligning words in the chunks, and by using them in the speech-to-speech machine translation, the ambiguities of spoken language word alignment can be decreased by using the integrality of chunks.

Abstract: The present invention provides a method and apparatus for training a target language word inflection (TLWI) model based on a bilingual corpus, a TLWI method and apparatus, and a translation method and system for translating a source language text into a target language translation. In the method for training a TLWI model based on a bilingual corpus, the bilingual corpus includes a plurality of aligned corpus pairs of source language and target language, the method comprises building an initial TLWI model, pre-processing the source language corpus and the target language corpus, extracting patterns containing TLWI information, based on the pre-processed source language corpus and the target language corpus, and training the TLWI model by using the patterns.

Abstract: There is provided a method for translating a speech, includes recognizing the speech into a text which includes a long sentence containing a plurality of simple sentences, segmenting the long sentence into the simple sentences, and translating each simple sentence into a sentence of a target language. A long sentence segmentation module is inserted between the speech recognition module and the machine translation module in the method, wherein the long sentence in the text recognized can be split into several simple and complete sentences. In this way, difficulties in translation are relieved, and translation quality is improved. Further, there is also provided a user interface which allows the user to modify the segmentation results conveniently. The modifying operations of the user are recorded to update the segmentation model online to improve the effect of the automatic segmentation step by step.