MIRA

There has been a proliferation of recent work on SMT tuning algorithms capable of han- dling larger feature sets than the traditional MERT approach. We analyze a number of these …...

We study a problem with pairwise ranking optimization (PRO): that it tends to yield too short translations. We find that this is partially due to the inadequate smoothing in PRO’s …...

General natural language processing and text-to-speech applications require certain (lexical level) processing steps in order to solve some frequent tasks such as lemmatization, syllabification, lexical stress prediction and phonetic transcription. …...

Parameter tuning is an important problem in statistical machine translation, but surpris- ingly, most existing methods such as MERT, MIRA and PRO are agnostic about search, while search errors could …...

We present APRO, a new method for machine translation tuning that can handle large feature sets. As opposed to other popular methods (e.g., MERT, MIRA, PRO), which involve ran- domness …...

The log-linear combination of different features is an important component of SMT systems. It allows for the easy in- tegartion of models into the system and is used during decoding …...

In this paper, we describe our submis- sion to WMT 2015 Tuning Task. We integrate a dependency-based MT evalu- ation metric, RED, to Moses and com- pare it with BLEU …...

Parameter tuning is a key problem for sta- tistical machine translation (SMT). Most popular parameter tuning algorithms for SMT are agnostic of decoding, result- ing in parameters vulnerable to search …...