The effectiveness of translation memory for computer-aided translation depends on the results of previous sentence alignment. This paper describes a new approach to sentence alignment, based on a crosslingual querying using the technology of an existing product, SPIRIT (Syntactic and Probabilistic Indexing and Retrieval of Information in Texts). Sentence alignment and crosslingual querying base...

This paper addresses automatic detection of dependencies between Japanese phrasal units called bunsetsus, and sentence boundaries in a spontaneous speech corpus. In spontaneous speech, the biggest problem with dependency structure analysis is that sentence boundaries are ambiguous. In this paper, we propose two methods for improving the accuracy of sentence boundary detection in spontaneous Jap...

Statistical machine translation models are trained from parallel corpora, which are collections of translated texts. These texts are usually processed using dedicated tools called “sentence aligners”, which output parallel sentence pairs. However, parallel resources are very scarce in certain languages or domains. Alternative solutions have been proposed that extract parallel sentences from the...

Sentence embedding is an influential research topic in natural language processing (NLP). Generation of sentence vectors that reflect the intrinsic meaning sentences crucial for improving performance various NLP tasks. Therefore, numerous supervised and unsupervised sentence-representation approaches have been proposed since advent distributed representation words. These evaluated on semantic t...