Yevgeny Ludovik

Fixing paper assignments

  1. Please select all papers that belong to the same person.
  2. Indicate below which author they should be assigned to.
Provide a valid ORCID iD here. This will be used to match future papers to this author.
Provide the name of the school or the university where the author has received or will receive their highest degree (e.g., Ph.D. institution for researchers, or current affiliation for students). This will be used to form the new author page ID, if needed.

TODO: "submit" and "cancel" buttons here

2000

pdf bib
The Week at a Glance - Cross-language Cross-document Information Extraction and Translation
Jim Cowie | Yevgeny Ludovik | Hugo Molina-Salgado | Sergei Nirenburg
COLING 2000 Volume 2: The 18th International Conference on Computational Linguistics

pdf bib
MT and Topic-Based Techniques to Enhance Speech Recognition Systems for Professional Translators
Yevgeny Ludovik | Ron Zacharski
COLING 2000 Volume 2: The 18th International Conference on Computational Linguistics

1999

pdf bib
Multilingual document language recognition for creating corpora
Yevgeny Ludovik | Ron Zacharski
Proceedings of Machine Translation Summit VII

In this paper we describe a language recognition algorithm for multilingual documents that is based on mixed-order n-grams, Markov chains, maximum likelihood, and dynamic programming. We present the results of an experimental study that showed that the performance of this algorithm has practical value.

pdf bib
Using a target language model for domain independent lexical disambiguation
Jim Cowie | Yevgeny Ludovik | Sergei Nirenburg
Proceedings of Machine Translation Summit VII

In this paper we describe a lexical disambiguation algorithm based on a statistical language model we call maximum likelihood disambiguation. The maximum likelihood method depends solely on the target language. The model was trained on a corpus of American English newspaper texts. Its performance was tested using output from a transfer based translation system between Turkish and English. The method is source language independent, and can be used for systems translating from any language into English.
Search
Co-authors
Venues
Fix data