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Areesha Maqsood

FAST · 2022 · I18 - 0600
Email
Phone
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Academic

Program
BSCS
CGPA
Year
2022
Education
SEECS
Address
DOB

Career

Current role
Target role
Skills
Flutter, Google Firebase, Librosa, Torch, Google Search API, Beautiful Soup, Python, Google Colab, Urdu Speech Recognition, Machine Learning

Verbatim text

The exact text the LLM saw on the page (or the booklet text from the old import). This is what powers semantic search.
Smart Grocery 

Our Project is based on the idea of ordering groceries online through Urdu Speech Recognition as 
well as making a user profile for further saving the user’s most frequently ordered items and 
categorizing edible items that would be safe or unsafe for the user (in case of any health issues).  
In our project for Urdu speech recognition, we will have to train and develop an Urdu based speech 
recognition model by first using multiple voice recordings as datasets and mapping them out with 
their corresponding English text by transcribing them. The problem that we discovered was that 
Urdu doesn't have a global recognition as a language despite there being 70 million native speakers. 
So, by enabling Urdu Speech we would be promoting an application that has the ability to 
understand what a native Urdu speaker is trying to order. 
The next feature is Auto Generation, for this we will have to collect data of a user’s recent 
purchases as well as their frequently bought items, next after collecting a sufficient amount of data, 
a grocery list will be generated which matches the user profile. The objective of this is to minimize 
the amount of time a user takes to select every grocery item on their shopping list. So, generating a 
grocery list will help users order groceries with less effort and time. Also, to facilitate the users 
more, Smart Categorization will help users be shown only edible products that would be medically 
safe for the user based on their health requirements. The problem that we discovered was that, 
most people cannot differentiate edible items that would be medically safe or unsafe for them, 
they would tend to ignore labels on food items or even general research on a particular item. So, smart categorization would allow for users to be displayed edible items that are safe for them. 





Technology Used: 
Flutter, Google Firebase, Librosa, Torch, Google 
Search API, Beautiful Soup, Python, Google Colab 
Supervisor Name: 
Dr. Shujaat Hussain 
Group Members:   
Shujaa Marwat (I18 - 0432) 


Kamal Qureshi (I18 - 0438) 
Areesha Maqsood (I18 - 0600)

AI enrichment

Areesha Maqsood is a BSCS student who contributed to a capstone project involving an Urdu speech recognition grocery ordering system. The project utilized Flutter, Python, and machine learning libraries to implement speech-to-text, user profiling, and health-based product categorization.
Skills (AI)
["Flutter", "Python", "Google Firebase", "Librosa", "PyTorch", "Google Search API", "Beautiful Soup", "Urdu Speech Recognition", "Machine Learning"]
Status: ai_done
Provenance
Source file: Graduate Directory FAST School of Computing 2022 Final Version (07-06-2022).pdf
From job #25 page 259
Created: 1778149999