LIP READING DRIVEN DEEP LEARNING APPROACH FOR SPEECH ENHANCEMENT
1. Introduction: One-page introduction of your project.
2. Literature Review Summary Table
Kindly go through projects, review papers related to your project and study them. A minimum of at least five projects/papers should be reviewed so that you have a considerable understanding of what is achieved in your project area. should be well defined with clear background information along with unique features of your project.
. Innovation component in the project: The most innovative part of your project should be explained. How does your project defer from others and the routine experimental results?
5. Work done and implementation
a. Methodology adapted: The Methodology used should be discussed in detail. Hardware and software requirements must also be mentioned.
b. Dataset used:
- a. Where are you taking your dataset? Narrow down your data to what is needed.
- b. Is your project based on any other reference project (Stanford Univ. or MIT)?
- c. How does your project differ from the reference project?
c. Tools used: Clear and concise explanation as to why you selected a tool and how you used it.
d. Pre-processing involved: Steps involved in preprocessing.
e. Models used: Description of the models used. Justify your choice of model. Highlight how class imbalance was dealt with?
f. Model Architecture: Model description along with complete architecture diagram. Highlight the detailed design showing the system design with components/modules/parts/layers etc of your project.
g. Screenshot and Demo along with Visualization (For results): Each model result and necessary coding part should be substantiated with a related screenshot.
6. Comparison, Results, and discussion along with Visualization Results of each model must be given separately, and a comparison of the models in terms of performance must be carried out. Results given should be as detailed as possible along with suitable visualization and sufficient discussion is included in the report.