Hizlaria: Lluis Màrquez
…………….Arabic Language Technologies group from the Qatar Computing Research
Eguna: Ekainaren 15ean, ostegunean
Ordua: 12:00
Gela: 3.2 gela. Informatika Fakultatea (UPV/EHU)

Hitzaldiaren izenburua: “Discourse Structure in Machine Translation Evaluation / Diskurtsoaren egitura itzulpen automatikoaren ebaluazioan”

Atzo egin genuen sariaren zozketa, 1549 zenbakia izan zen saritua. Itzulpengintza eta Interpretazioa Gradua ikasten duen Garazi Urraka-ri tokatu zaio. Zorionak.

Nire aldetik, eskerrak eman nahi dizkizuet zuen parte hartzeagatik, laguntzagatik eta pazientziagatik. Emaitzak… laster.
Eskerrik asko,

Nora Aranberri

Gaia: Automatic Projection of Semantic Structures: an Application to Pairwise Translation Ranking  (Rol semantikoen erabilera itzulpenen kalitatea neurtzerakoan.)
Tokia: 3.2 gelan (batzar-gela ohia)
Hizlaria: Daniele Pighin
Eguna: Maiatzaren 31
Ordua: 11:30

Izenburua / Title
Automatic Projection of Semantic Structures: an Application to Pairwise Translation Ranking
(Rol semantikoen erabilera itzulpenen kalitatea neurtzerakoan.)

Laburpena /Abstract
The ability to automatically assess the quality of translation hypotheses is a key requirement towards the development of accurate and dependable translation models. While it is largely agreed that proper transfer of predicate-argument structures from source to target is a very strong indicator of translation quality, especially in relation to adequacy, the incorporation of this kind of information in the Statistical Machine Translation (SMT) evaluation pipeline is still limited to few and isolated cases.

We present a model for the inclusion of semantic role annotations in the framework of confidence estimation for machine translation. The model has several interesting properties:

1. it only requires a linguistic processor on the (generally well-formed) source side of the translation;
2. it does not directly rely on properties of the translation model (hence, it can be applied beyond phrase-based systems);
3. it is inherently extendable to cope with different kinds of sequential annotations, e.g., POS tags.

These features make it potentially appealing for system ranking, translation re-ranking and user feedback evaluation. Preliminary experiments in pairwise hypothesis ranking on five confidence estimation benchmarks show that the model has the potential to capture salient aspects of translation quality.

Laburpena:
Automatic evaluation plays a very important role in the development andcomparison of machine translation systems. In this talk we will overview the current trend of using linguistically-guided evaluation measures based on several linguistic layers and their combination.
Also, we will talk about confidence estimation measures, a particular subset of measures to assess output quality without the need of reference translations. Finally, we will overview the role of evaluation measures within the FAUST European project (Feedback Analysis for User Adaptive Statistical Translation; http://www.faust-fp7.eu/), focusing on the usage of user feedback to guide the combination of measures.