Sampling-based multilingual alignment
Year: 2009
Type: conference-paper
Abstract: We present a sub-sentential alignment method that extracts high quality multi-word alignments from sentence-aligned multilingual parallel corpora. Unlike other methods, it exploits low frequency terms, which makes it highly scalable. As it relies on alingual concepts, it can process any number of languages at once. Experiments have shown that it is competitive with state-of-the-art methods.
Source: HAL
Authors: Lardilleux, Adrien, Lepage, Yves
Institution: GREYC
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2159712545