Idea Details

Team and Contact Details

SNo Student Name School Degree Year Email
1Syeda Urooj FatimaSEECSUndergraduateFourthsfatima.bese15seecs@seecs.edu.pk
1Danial AhmedSEECSUndergraduateFourthdahmed.bese15seecs@seecs.edu.pk
1Aqsa NadeemSEECSUndergraduateFourthanadeem.bese15seecs@seecs.edu.pk

Inter School Idea ? No
Do you need expertises from another area: No
If Yes please provide details of expertises you need:

Idea Details

Idea Name: EmoFehm
Slogan: Say no to miscommunication
Supervisor Name: Dr Omar Arif
Supervisor Designation: Associate Professor
Supervisor School: SEECS
Supervisor Department: DOC
Contact number: 03475174193
Email ID: omar.arif at seecs.edu.pk
Abstract:
    Words portray different meaning when used in different textual context. In distant communications a message might not be conveyed across in its real sense, depicting an unwanted impression on receiving end. We are creating a system that predicts the emotion from text using techniques of Natural Language Processing and Deep Learning, that will help to solve the aforementioned problem.
What is the unmet need in society that your idea will fulfill ?
    It is the era of social media. Most of the communication is being done via text. In case of formal communications, a person has to be careful about his tone. Text may potray a wrong emotion leading to miscommunication. Emo fehm will recognize the emotion and user can alter the message accordingly.
Who needs it ? How many would benefit ?
   Emofehm can be used by students during their formal communications with teacher or while writing an application for exchange programs and other universities. Another potential customer of emofehm is employees while communicating with the boss. It can also be used by brands for public opinion mining
How will the solution works
    we aim to devise an intelligent system (Application as well as website) that will classify emotion of the person given the text input using natural language processing techniques and deep neural networks. The approach can be broadly outlined as: Product Feasibility Study. Gathering of Data (text). Apply Deep Neural Networks on the data gathered as a Classification Algorithm. Emotion classification Visualization of Results. Application Development
Who are your competitors ? How is your solution different
    Our competitors are different emotion recognition APIs available online. Our product is different because it provides accurate results and the available tools are not easily integrated with email while we provide extension and app which is easy to use. Our product is trained on generic data.
Status: new
Entry Date & Time: 2018-12-23 (1852)