Many NLP applications need fundamental tools to convert the input text into appropriate form or format and extract the primary linguistic knowledge of words and sentences. These tools perform segmentation of text into sentences, words and phrases, checking and correcting the spellings, doing lexical and morphological analysis, POS tagging and so on. Persian is among languages with complex prepr...

BACKGROUND Neural correlates of single word reading with the use of a functional MRI (fMRI) scan have been widely studied in different languages. These study patterns of cortical activation differ in different languages. In this report we used a similar technique to study cortical activation when reading single Persian words. METHODS The subjects were comprised of nine healthy right-handed bi...

Persian clitic groups differ from words. Most importantly, a pitch accent (L+)H* is associated with the word-final (i.e. base-final) syllable of clitic groups, but with the word-final syllable of words, meaning that clitics remain outside the domain of the word. The pitch accent marks the stress, but we found no independent durational or spectral differences between stressed and unstressed syll...

The interest in text to speech synthesis increased in the world . text to speech have been developed for many popular languages such as English, Spanish and French and many researches and developments have been applied to those languages. Persian on the other hand, has been given little attention compared to other languages of similar importance and the research in Persian is still in its infan...

The cursive nature of Persian alphabet, and the complex and convoluted rules regarding this script cause major challenges to segmentation as well as recognition of Persian words. We propose a new segmentation algorithm for the main stroke of online Persian handwritten words. Using this segmentation, we present a perturbation method which is used to generate artificial samples from handwritten w...

Plagiarism detection is defined as automatic identification of reused text materials. General availability of the internet and easy access to textual information enhances the need for automated plagiarism detection. In this regard, different algorithms have been proposed to perform the task of plagiarism detection in text documents. Due to drawbacks and inefficiency of traditional methods and l...

In order to facilitate sentiment analysis of Persian text, we’ve designed and implemented an algorithm which aims to detect words with negative polarity. Currently most sentiment analysis algorithms depend mainly on polarity datasets. However, since negative prefixes in Persian are only attached to a semantically positive base (shaghagi, 2002), we have incorporated a negative prefix detection t...

In this paper, we describe our proposed method for measuring semantic similarity for a given pair of words at SemEval2017 monolingual semantic word similarity task. We use a combination of knowledge-based and corpus-based techniques. We use FarsNet, the Persian WordNet, besides deep learning techniques to extract the similarity of words. We evaluated our proposed approach on Persian (Farsi) tes...

Stemmers are softwares that find syntactic` roots of the words. They play an important role in natural language processing and other fields such as information retrieval (IR). In IR using stemmed words instead of the original words, could increase as much as 15 percent to the overall performance. In this paper, we report on the development of the first Persian stemmer (Bon). Bon is tested on a ...