In this paper we describe and evaluate the corpora submitted to the PAN 2015 shared task on plagiarism detection for text alignment. We received monoand cross-language corpora in the following languages (pairs): English, Persian, Chinese, and Urdu-English, English-Persian. We present an independent section for each submitted corpus including statistics, discussion of the obfuscation techniques ...

In this paper we describe and evaluate the corpora submitted to the PAN 2015 shared task on plagiarism detection for text alignment. We received monoand cross-language corpora in the following languages (pairs): English, Persian, Chinese, and Urdu-English, English-Persian. We present an independent section for each submitted corpus including statistics, discussion of the obfuscation techniques ...

Viseme (Visual Phoneme) clusterin every language is among the most important conducting various multimedia researches as reading, lip synchronization and com pronunciation training applications. With re that clustering and analyzing visemes are lan processes, we concentrated our research on P which indeed has suffered from lack of su paper, we used a hierarchical approach for c in Persian langu...

Low-density languages raise difficulties for standard approaches to natural language processing that depend on large online corpora. Using Persian as a case study, we propose a novel method for bootstrapping MT capability for a low-density language in the case where it relates to a higher density variant. Tajiki Persian is a low-density language that uses the Cyrillic alphabet, while Iranian Pe...

In this paper, we investigate the problem of Ezafe recognition in Persian language. Ezafe is an unstressed vowel that is usually not written, but is intelligently recognized and pronounced by human. Ezafe marker can be placed into noun phrases, adjective phrases and some prepositional phrases linking the head and modifiers. Ezafe recognition in Persian is indeed a homograph disambiguation probl...

This paper reports the present results of a research on unsupervised Persian morpheme discovery. In this paper we present a method for discovering the morphemes of Persian language through automatic analysis of corpora. We utilized a Minimum Description Length (MDL) based algorithm with some improvements and applied it to Persian corpus. Our improvements include enhancing the cost function usin...

Word Sense Disambiguation has long been a central problem in computational linguistics. Word Sense Disambiguation is the ability to identify the meaning of words in context in a computational manner. Statistical and supervised approaches require a large amount of labeled resources as training datasets. In contradistinction to English, the Persian language has neither any semantically tagged cor...