Convergence of Translation Memory and Statistical Machine Translation
نویسندگان
چکیده
We present two methods that merge ideas from statistical machine translation (SMT) and translation memories (TM). We use a TM to retrieve matches for source segments, and replace the mismatched parts with instructions to an SMT system to fill in the gap. We show that for fuzzy matches of over 70%, one method outperforms both SMT and TM baselines.
منابع مشابه
A new model for persian multi-part words edition based on statistical machine translation
Multi-part words in English language are hyphenated and hyphen is used to separate different parts. Persian language consists of multi-part words as well. Based on Persian morphology, half-space character is needed to separate parts of multi-part words where in many cases people incorrectly use space character instead of half-space character. This common incorrectly use of space leads to some s...
متن کاملThe Correlation of Machine Translation Evaluation Metrics with Human Judgement on Persian Language
Machine Translation Evaluation Metrics (MTEMs) are the central core of Machine Translation (MT) engines as they are developed based on frequent evaluation. Although MTEMs are widespread today, their validity and quality for many languages is still under question. The aim of this research study was to examine the validity and assess the quality of MTEMs from Lexical Similarity set on machine tra...
متن کاملTranslation Technology Tools and Professional Translators’ Attitudes toward Them
Today technology is an integral part of professional translation; and it is generally assumed that translators’ attitudes toward translation technology tools influence their interaction with technology (Bundgaard, 2017). Therefore, the present two-phase study seeks to shed some light on what translation technology tools are and how professional translators feel toward them. The research method ...
متن کاملA Hybrid Machine Translation System Based on a Monotone Decoder
In this paper, a hybrid Machine Translation (MT) system is proposed by combining the result of a rule-based machine translation (RBMT) system with a statistical approach. The RBMT uses a set of linguistic rules for translation, which leads to better translation results in terms of word ordering and syntactic structure. On the other hand, SMT works better in lexical choice. Therefore, in our sys...
متن کاملA Coactive Learning View of Online Structured Prediction in Statistical Machine Translation
We present a theoretical analysis of online parameter tuning in statistical machine translation (SMT) from a coactive learning view. This perspective allows us to give regret and generalization bounds for latent perceptron algorithms that are common in SMT, but fall outside of the standard convex optimization scenario. Coactive learning also introduces the concept of weak feedback, which we app...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2010