Two methods using comparable corpora to select translation equivalents appropriate to a domain were devised and evaluated. The first method ranks translation equivalents of a target word according to similarity of their contexts to that of the target word. The second method ranks translation equivalents according to the ratio of associated words that suggest them. An experiment using the EDR bi...

We explore the use of segments learnt using Byte Pair Encoding (referred to as BPE units) as basic units for statistical machine translation between related languages and compare it with orthographic syllables, which are currently the best performing basic units for this translation task. BPE identifies the most frequent character sequences as basic units, while orthographic syllables are lingu...

Previous work has shown that pseudo relevance feedback (PRF) can be effective for cross-lingual information retrieval (CLIR). This research was primarily based on corpora such as news articles that are written using relatively formal language. In this paper, we revisit the problem of CLIR with a focus on the problems that arise with informal text, such as blogs and forums. To address the proble...

A Translation Invariance Denoising Algorithm with Wavelet Threshold and its Application on Signal Processing of Laser Interferometer Hydrophone is investigated. The obtained signal of Laser interferometer hydrophone exist a large number of singularity points, and the denoising algorithm of Donoho’s wavelet threshold may produce the Pseudo Gibbs phenomenon on the singularity points. To eliminate...

We present an unsupervised method for word sense disambiguation that exploits translation correspondences in parallel corpora. The technique takes advantage of the fact that cross-language lexicalizations of the same concept tend to be consistent, preserving some core element of its semantics, and yet also variable, reeecting diier-ing translator preferences and the in-uence of context. Working...

Low-resource languages often face the problem of insufficient data, which leads to poor quality in machine translation. One approach address this issue is data augmentation. Data augmentation involves creating new by transforming existing through methods such as flipping, cropping, rotating, and adding noise. Traditionally, pseudo-parallel corpora are generated randomly replacing words low-reso...