Sharif Digital Repository

The utilizing language model is one of the most effective methods for improving speech recognition performance. For speech recognition applications, several types of language models have been proposed for speech recognition applications that try to model some parts of language information, such as n-gram models, syntactic models, and semantic models. Although n-gram, syntactic and semantic models are able to model different structures that exist in natural language, they each only capture specific linguistic phenomena. None of them can simultaneously take into account all of language phenomena in a unified probabilistic framework. Recently, a number of semantic models called "latent topic... 

Question answering systems are systems which get a question in natural language as input and present an explicit, appropriate answer to the question. One of the major components of automatic question answering systems is question processing component in which the input question is analyzed. The main goal of question processing phase is to determine the answer type through question classification. Rule-based, machine learning-based and hybrid approaches have been used in order to develop question classifiers among which machine learning-based ones have outperformed the others. This study’s main goal is to develop a question classifier for Persian open domain question answering systems.... 

Pronoun resolution is one of the challenges of natural language processing. The proposed solutions range from heuristic rule-based to machine learning data driven approaches. In this thesis, we followed a previous machine learning base work to Persian pronoun anaphora resolution. The primary goal of this thesis was to improve results, mainly by extracting more balanced data and to add more features to the extracted feature vectors used in classification. Using PCAC2008 dataset, we considered noun phrase structure as a way to extract more suitable training data. Features added to the extracted data include syntactic and semantic features. Then, we trained and tested different machine learning... 

This study attempts to introduce a novel approach to abstractive summarization in Persian. According to the methodology the first step is to represent input text sentences into an abstract meaning representation structure. This representation is syntax free thus, it helps the summarization system to represent sentences more semantic based and free of the sentence syntactic structure. In order to select suitable content for the summary output semantic and structural features are extracted from the representation. Data used in this research consists of approximatelty 200 senctences summarized in 30 sentences of a famous story book named: ”The little prince”. An SVM is trained on 80% of... 

With the rapid development of communication technology, the importance of information security is growing daily. Data Encryption, as one of the most important tools of secure communication, has attracted a lot of attention. Most conventional cryptography methods are based on computational complexity assumptions. Hence, they are threatened by computational power enhancements. One of the most important approaches of cryptography that does not have this drawback is quantum cryptography. The unconditional security of this method has been proved by laws of quantum mechanics. One application of quantum cryptography is quantum key distribution that enables secret key exchange between two users. The... 

In this study, first a set of data was colleted which consisted of colloquial sentences in Persian. Each of these sentences was rendered into standard Persian by native speakers. As a result, a corpus of parallel data including 1698 pairs of sentences was created. Then each colloquial sentence and its formal equivalent were converted into term-frequency vectors and the cosine distance similarity between the two vectors was calculated. Besides the mean and the standard deviation of all cosine distances were obtained. Afterwards the whole set of data was divided into two halves through Stratified randomization so that the two halves resembled each other in terms of cosine distance similarity.... 

The most common form of communication on the internet and social network websites is text messages. normally communication on social media or even on the web is by posting some sort of text. usually, these messages or posts are short and text used in them may not follow any language standards, this makes it very difficult to process them. Different age groups use a certain language differently and this is shown in the way, each of them writes texts. The advancements made in the field of natural language processing and computational linguistics makes it possible to predict, text authors age groups by analyzing the way they write. This study focuses on ways to automatically recognize the age... 

There are different types of media bias. The aim of this study is to analyze media bias by considering two types of it: selection (or coverage) bias and language bias. Thus we have collected some specific news stories or articles -which contain “Iran” as a keyword- from the websites of four news broadcasters that are Al Arabiya, Deutsche Welle (DW), Radio France Internationale (RFI) and SPUTNIK, to build text datasets. For the purpose of comparing and analyzing media bias, the news had to be gathered during two time frames before and after the day the P5+1, European Union and Iran reached Joint Comprehensive Plan of Action (JCPOA). Finally, the collected corpora have amounted to 784 news... 

In this thesis, I try to use methods and algorithms of computational linguistics and natural language processing for textual criticism of Persian manuscripts' texts and design and develop a software based on that. Suggested method in this thesis is comparing all manuscripts' texts with base manuscript's text by Dynamic Time Warping (DTW) algorithm, after definition of base manuscript. Then the same sentences are extracted in different manuscripts and POS tagged as body of corpus of author's style and learned as language model by Hidden Markov Model (HMM). At next stage, due to the textual criticism's rules and using of author stylistics algorithms choose the case which is most similar to the... 

The interest in analyzing human language with complex networks is on the rise in recent years and a considerable body of research in this area has already been accumulated.However unfortunately, the use of applications of complex networks in Persian Linguistics research is missing. With the goal of introducing complex networks and their applications in this field, two of these applications have been studied in this research. First, we tried to build an inclusive network model, considering two levels of Syntax and Word Cooccurrence, for the Persian Language and provide Linguistics interpretations for them. In addition, by comparing co-occurrence networks of different languages, garnered from...