Bayesian Adaptation for Statistical Machine Translation

نویسندگان

  • Germán Sanchis-Trilles
  • Francisco Casacuberta
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Online adaptation strategies for statistical machine translation in post-editing scenarios

One of the most promising approaches to machine translation consists in formulating the problem by means of a pattern recognition approach. By doing so, there are some tasks in which online adaptation is needed in order to adapt the system to changing scenarios. In the present work, we perform an exhaustive comparison of four online learning algorithms when combined with two adaptation strategi...

متن کامل

Log-linear weight optimisation via Bayesian Adaptation in Statistical Machine Translation

We present an adaptation technique for statistical machine translation, which applies the well-known Bayesian learning paradigm for adapting the model parameters. Since state-of-the-art statistical machine translation systems model the translation process as a log-linear combination of simpler models, we present the formal derivation of how to apply such paradigm to the weights of the log-linea...

متن کامل

Learning from Post-Editing: Online Model Adaptation for Statistical Machine Translation

Using machine translation output as a starting point for human translation has become an increasingly common application of MT. We propose and evaluate three computationally efficient online methods for updating statistical MT systems in a scenario where post-edited MT output is constantly being returned to the system: (1) adding new rules to the translation model from the post-edited content, ...

متن کامل

Alignment Inference and Bayesian Adaptation for Machine Translation

We propose a flexible and efficient domain adaptation method that yields consistent improvements in machine translation (for 11 language pairs). The idea is to decompose the word alignment process into two steps, model training and alignment inference, and perform Bayesian adaptation on the latter. This modularity allows one to incorporate out-of-domain data without the need to modify existing ...

متن کامل

Rapid Unsupervised Topic Adaptation – a Latent Semantic Approach

In open-domain language exploitation applications, a wide variety of topics with swift topic shifts has to be captured. Consequently, it is crucial to rapidly adapt all language components of a spoken language system. This thesis addresses unsupervised topic adaptation in both monolingual and crosslingual settings. For automatic speech recognition we rapidly adapt a language model on a source l...

متن کامل

ذخیره 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