Aligning Turkish and English Parallel Texts for Statistical Machine Translation
نویسندگان
چکیده
This paper presents a preliminary work on aligning Turkish and English parallel texts towards developing a statistical machine translation system for English and Turkish. To avoid the data sparseness problem and to uncover relations between sublexical components of words such as morphemes, we have converted our parallel texts to a morphemic representation and then used standard word alignment algorithms. Results from a mere 3K sentences of parallel English–Turkish texts show that we are able to link Turkish morphemes with English morphemes and function words quite successfully. We have also used the Turkish WordNet which is linked with the English WordNet, as a bootstrapping dictionary to constrain root word alignments.
منابع مشابه
Sentence Alignment of Brazilian Portuguese and English Parallel Texts
Parallel texts – texts in one language and their translations to other languages – are becoming more and more available nowadays on the Web. Aligning these texts means to find some correspondence between them, in sentence level, for instance. In this paper we describe some experiments done with Brazilian Portuguese and English parallel texts using five well known sentence alignment methods. The...
متن کاملAligning and Using an English-Inuktitut Parallel Corpus
A parallel corpus of texts in English and in Inuktitut, an Inuit language, is presented. These texts are from the Nunavut Hansards. The parallel texts are processed in two phases, the sentence alignment phase and the word correspondence phase. Our sentence alignment technique achieves a precision of 91.4% and a recall of 92.3%. Our word correspondence technique is aimed at providing the broades...
متن کاملInitial Explorations in English to Turkish Statistical Machine Translation
This paper presents some very preliminary results for and problems in developing a statistical machine translation system from English to Turkish. Starting with a baseline word model trained from about 20K aligned sentences, we explore various ways of exploiting morphological structure to improve upon the baseline system. As Turkish is a language with complex agglutinative word structures, we e...
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 کاملUsing Transliteration of Proper Names from Arabic to Latin Script to Improve English-Arabic Word Alignment
Bilingual lexicons of proper names play a vital role in machine translation and cross-language information retrieval. Word alignment approaches are generally used to construct bilingual lexicons automatically from parallel corpora. Aligning proper names is a task particularly difficult when the source and target languages of the parallel corpus do not share a same written script. We present in ...
متن کامل