Word Alignment Model

This paper presents a new model for word align- ments between parallel sentences, which allows one to accurately estimate different parameters, in a computationally efficient way. An applica- tion of …...

This paper presents a new model for word align- ments between parallel sentences, which allows one ~o accurately estimate different parameters, in a computationally efficient way. An applica- tion of …...

. In statistical machine translation, word alignment models are trained on bilingual corpora. Long sentences pose severe problems: 1. the high computational requirements; 2. the poor quality of the resulting …...

We present a novel statistical approach to semantic parsing, WASP, for construct- ing a complete, formal meaning represen- tation of a sentence. A semantic parser is learned given a set …...

We introduce a syntactically enhanced word alignment model that is more flex- ible than state-of-the-art generative word alignment models and can be tuned ac- cording to different end tasks. First …...

Current word alignment models for statisti- cal machine translation do not address mor- phology beyond merely splitting words. We present a two-level alignment model that dis- tinguishes between words and …...

This study proposes a word alignment model based on a recurrent neural net- work (RNN), in which an unlimited alignment history is represented by re- currently connected hidden layers. We …...

AbstractHuman conversations contain many types of information, e.g., knowledge, common sense, and language habits. In this paper, we propose a conversational word embedding method named PR-Embedding, which utilizes the conversation …...

AbstractIn this paper, we describe our submissions to the WMT20 shared task on parallel corpus filtering and alignment for low-resource conditions. The task requires the participants to align potential parallel …...