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# Juan Antonio Pérez-Ortiz

2 paper cards in Mova's library · 2011–2020

Juan Antonio Pérez-Ortiz wrote 2 of the papers Mova reads, in 2011–2020, most of them on [Machine translation](https://md.mova.elamur.ai/free/en/docs/papers/topics/machine-translation/); often with [Felipe Sanchez-Martinez](https://md.mova.elamur.ai/free/en/docs/papers/authors/felipe-sanchez-martinez/), Rafael C. Carrasco, Víctor M. Sánchez-Cartagena.

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Juan+Antonio+P%C3%A9rez-Ortiz) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Juan+Antonio+P%C3%A9rez-Ortiz) · [dblp](https://dblp.org/search?q=Juan+Antonio+P%C3%A9rez-Ortiz) · [ACL Anthology](https://aclanthology.org/search/?q=Juan+Antonio+P%C3%A9rez-Ortiz) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Juan+Antonio+P%C3%A9rez-Ortiz)

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

## Ideas Mova took (1)

From the ideas ledger: an idea tried, kept or queued, or measured with no gain, and what it gave.

- **tried** — A count test for lexicon merges. Merge two concepts (or two meta tokens) only when their proportions over the same contexts agree under a dissimilarity like the paper's, computed from counts. This targets open problem 2. Measure the merges kept, including… *([Learning synchronous context-free grammars with multiple…](https://md.mova.elamur.ai/free/en/docs/papers/sanchez-2020-martinez-learning-synchronous-context-free-grammars/) · translate r6-lb: a count/lower-bound test for merges (with riding-2008 I1); kept)*

## Papers

1. **[Learning synchronous context-free grammars with multiple specialised non-terminals for hierarchical phrase-based translation](https://md.mova.elamur.ai/free/en/docs/papers/sanchez-2020-martinez-learning-synchronous-context-free-grammars/)** *(2020)* Hierarchical phrase-based translation uses one nonterminal, which the authors take to be overloaded. They give every gap of every extracted phrase pair its own nonterminal, which yields about 850,000 nonterminals on a small English-Spanish EMEA corpus (sentences up to 20 words). Two nonterminals are then merged when…
2. **[Integrating shallow-transfer rules into phrase-based statistical machine translation](https://md.mova.elamur.ai/free/en/docs/papers/cartagena-2011-integrating-shallow-transfer-rules-into/)** *(2011)* A hybrid method that feeds a phrase-based statistical system with the knowledge of a shallow-transfer rule system.

## Co-authors (3)

- [Felipe Sanchez-Martinez](https://md.mova.elamur.ai/free/en/docs/papers/authors/felipe-sanchez-martinez/) ×2
- Rafael C. Carrasco
- Víctor M. Sánchez-Cartagena
- [← previous Joshua Guedalia](https://md.mova.elamur.ai/free/en/docs/papers/authors/joshua-guedalia/)
- [next → Judith Degen](https://md.mova.elamur.ai/free/en/docs/papers/authors/judith-degen/)
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