---
title: "Benoit Lavoie — papers and cards"
description: "Benoit Lavoie: 2 paper cards in the Research library (1997–2002), with what each paper is about, the ideas Mova took from it, and the co-authors."
canonical: "https://research.elamur.ai/free/en/authors/benoit-lavoie/"
---
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# Benoit Lavoie

2 paper cards in the Research library · 1997–2002

Benoit Lavoie wrote 2 of the papers Mova reads, in 1997–2002, most of them on [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/); often with [Michael White](https://md.research.elamur.ai/free/en/authors/michael-white/), Owen Rainbow, Tanya Korelsky.

[OpenAlex](https://openalex.org/A5016315862) · [**h-index 11**](https://openalex.org/authors/A5016315862) · [640 citations](https://openalex.org/authors/A5016315862) · [35 works](https://openalex.org/works?filter=author.id:A5016315862) — openalex-snapshot, 2026-10-14

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Benoit+Lavoie) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Benoit+Lavoie) · [dblp](https://dblp.org/search?q=Benoit+Lavoie) · [ACL Anthology](https://aclanthology.org/search/?q=Benoit+Lavoie) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Benoit+Lavoie)

Topics: [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/) 2

## Papers

1. **[Learning Domain-Specific Transfer Rules: An Experiment with Korean to English Translation](https://md.research.elamur.ai/free/en/papers/lavoie-2002-learning-domain-specific-transfer-rules/)** *(2002)* An MT system that learns lexico-structural transfer rules from parsed bitexts, for domain-specific Korean-to-English translation.
2. **[A Fast and Portable Realizer for Text Generation Systems](https://md.research.elamur.ai/free/en/papers/lavoie-1997-fast-portable-realizer-text-generation/)** *(1997)* A technical note on REALPRO, a C++ surface realiser built on Meaning-Text Theory. Its input is a deep-syntactic dependency tree of lexemes only: meaning-bearing words, labelled syntactic arcs, no function words, and no lexical choice, so the input fixes the output and the system is deterministic. Internally it runs a…

## Co-authors (3)

- [Michael White](https://md.research.elamur.ai/free/en/authors/michael-white/)
- Owen Rainbow
- Tanya Korelsky
