Department of Computer Engineering

Permanent URI for this communityhttps://repository.cuilahore.edu.pk/handle/123456789/15

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Start date: 2020Subject: search.filters.subject.Assistant Profesor

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    Travelholic
    (Library Information Services, COMSATS University, Lahore Campus, 2021) Khawaja Asad Gohar; FA17-BSE-137; Muhammad Junaid Anjum, Assistant Profesor; LHR TP 7017
    Imagine you want to visit someplace in Pakistan, and you don’t know what’s the easiest and cheapest way to get there. You need proper guidance to have a great trip without any hurdles. For this you’ll need proper and reliable information about hotels and transport services. Also, you need to convince yourself that why you should visit that place. Well, this application is all about that. In this application we’ll provide the travel enthusiast users all the reliable information and guidance they need to know before visiting any place in Pakistan. Users can either plan their own trip or they can opt for any of the trips offered and organized by “Travelholic” for tourist across Pakistan.
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    Developing a Speech Recognition System for the Urdu Language
    (Library Information Services, COMSATS University, Lahore Campus, 2021) Muhammad Ibtesam Arshad Hamza Safdar; FA17-BSE-061 FA17-BSE-013; Dr. Rao Muhammad Adeel Nawab, Assistant Profesor; LHR TP 7015
    Automatic Speech Recognition Systems (ASR) are used to convert the acoustic signals which are caught through the microphones into the sequence of words. The Automatic Speech Recognition Systems (ASR) empower the machines to react correctly, reliably, and effectively to human speech or voice and offer helpful and important services to the users. The interaction with computers or gadgets is faster, simpler, and easier, through voice or speech instead of typing through the keyboard or console, so the people will prefer Speech Recognition Systems. Speech Recognition Systems will facilitate the users in workplaces, in marketing, in banking, in health care, in language learning, and in the education field also. This project aims to design and the implementation a Speech Recognition System for the Urdu Language. In this first phase, we have collected data for the Urdu Language. To build a general Speech Recognizer, a huge amount of data is needed. In the second phase, we have implemented our System. In the final phase, we have trained and tested our Model. This model is Similar to Deep Speech 2 Models. The evaluation is carried out using Word Error Rate and Character Error Rate.
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    Sentiment Analysis on Current Government using Tweets
    (LHR TP 7032, 2021) Saman Azhar , Hamnna Ayemen , Areesha Ramzan,; FA17-BSE-036 , FA17-BSE-030 , FA17-BSE-062; M. Shahid Bhatti, Assistant Profesor; LHR TP 7022
    In the age of the internet, social media connects us all at the tip of our fingers. People are linked through different social media. The social network, Twitter, allows people to tweet their thoughts on any particular event or a specific political body, which provides us with a diverse range of political insights. This paper serves the purpose of (a) Natural Language Processing (NLP) of a multilingual dataset (Urdu, English, and Roman Urdu), (b) exploring machine learning solutions for sentiment analysis and training models, (c) collecting data on government from Twitter and applying sentiment analysis, and (d) providing a python library that classifies input texts as positive or negative. The training data contained tweets in three languages: English: 200000, Urdu: 200000, and Roman Urdu: 11099. Five different classification models are applied to determine sentiments, and eventually, the use of ensemble technique to move forward with the acquired results is explored. The Logistic Regression model performed best with an accuracy of 75%, followed by the Linear Support Vector classifier and the Stochastic Gradient Descent models, both having 74% accuracy. Lastly, the Multinomial Naïve Bayes and Complement Naïve Bayes models both had 73% accuracy.
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    Online Home Service (O.H.S)
    (Library Information Services, COMSATS University, Lahore Campus, 2020) Ahmad Usman Arshad , Fiza Naveed,; FA17-BSE-066 , FA17-BSE-142; Hafiz Muhammad Tahir, Assistant Profesor; LHR TP 7021
    The focus of the Online Home Services (OHS) web application is to facilitate the everyday consumer, while he/she looks for online services such as plumbing, car wash, etc. After a thorough research search over the internet, it was established that most of the websites offer a handful of services (see related work). This factor results in a situation where the consumers are scattered between websites, and unsatisfied, and they have a low probability of finding what they are looking for. This problem was handled through the OHS, as all the basic needs of the everyday consumer were determined through an in-depth study of various similar projects. This helped in the development of the website as it gave an overview of which services to add to the application and which are to be skipped. 11 of the major facilities were provided except for some, as the ones skipped were easily accessible to the consumer. One of the main concerns of the OHS is the competitive nature of the online market. However, as most of the e-commerce websites on the internet provide a limited set of services, the OHS is an innovation in the market and is projected to generate more internet traffic in a comparatively smaller period.