Project Blog
CS298
Week 12: May 4 - May 11
Minutes
- Submitted the final version of CS298 Project Report
- Finalized the CS298 defense slides
- Demonstrated end to end working of application
To Do
Week 12: Apr 27 - May 4
Minutes
- Successfully implemented Information Fusion Algorithm in application
- Evaluated initial draft of CS298 Project report
- Discussed about CS298 Defense Slides
To Do
- Finalize the CS298 Project report
- CS298 Defense Slides
Week 11: Apr 20 - Apr 27
Minutes
- Finalized Information Fusion technique (Fusion Algorithm) to calculate final emotion
- Discussed about CS298 final project report
To Do
- Implement information fusion algorithm in the application
- Start writing the initial draft of the report
Week 10: Apr 13 - Apr 20
Minutes
- Evaluated Information Fusion technique (Fusion Algorithm) based on multiple test cases
- Successfully calculated MFCCs using JLibrosa library
- Successfully deployed Speech Emotion recognition model on Android application
To Do
- Continue to research further about Information Fusion
- Test the application to predict facial and speech emotion
Week 9: Apr 6 - Apr 13
Minutes
- Discussed about Information Fusion technique (Fusion Algorithm) to calculate final emotion of the overall conversation
- Successfully installed JLibrosa library in the project
To Do
- Continue to research further about Information Fusion
- Calculate MFCCs using JLibrosa library
Week 8: Mar 30 - Apr 6
Minutes
- Discussed about deploying Speech Emotion Recognition tflite model on application
- Evaluated performance of the application
- Discussed about Android JLibrosa library to calculate MFCC
To Do
- Continue working on Android application
- Research about how to predict final emotion based on speech and face
- Install JLibrosa library in the project
Week 7: Mar 23 - Mar 30
Minutes
- Delivered the improved Speech Emotion Recognition Model
- Finalized which speech feature (MFCC) to use for Speech Emotion Recognition
To Do
- Continue working on Android application
- Convert the Keras Model to tflite model
Week 6: Mar 16 - Mar 23
Minutes
- Delivered initial Speech Emotion Recognition Model
- Discussed about the dependencies required to provide voice record feature in the application
- Reviewed the model architecture and discussed about improving the accuracy
To Do
- Continue working on Android application to provide speech support
- Continue to work on Speech Emotion Recognition Model to improve accuracy
Week 5: Mar 9 - Mar 16
Minutes
- Update regarding the Speech Emotion Recognition model
- Discussed about how to add a voice record feature in the application
- Discussed about converting the Keras model to tflite model
To Do
- Continue working on Android application to provide speech support
- Continue to develop the initial model to detect emotion based on speech
Week 4: Mar 2 - Mar 9
Minutes
- Explained the significance of MFCC, Chroma and Mel Spectrogram
- Demo of Android application with the functionality of recognizing emotion from both cameras
- Finalized the RAVDESS dataset for training and test the Speech Emotion Recognition Model
To Do
- Continue working on Android application to provide speech support
- Develop the initial model to detect emotion based on speech
Week 3: Feb 23 - Mar 2
Minutes
- Discussed about Speech Features (MFCC, Chroma, Mel Spectrogram)
- Android application update regarding frame captures
- Discussed about the dataset to use for Speech Emotion Recognition
To Do
- Continue working on Android application
- Understand the significance and weightage of each feature discussed in the meeting
Week 2: Feb 16 - Feb 23
Minutes
- Discussed about the speech recognition model and features of data
- Discussed about hybrid approach and decided the features to use for emotion recognition
To Do
- Continue working on Android application to capture frames
- Research about papers explaining the recognition of emotion using speech
Week 1: Feb 9 - Feb 16
Minutes
- Kick off meeting and further discussion of idea
- CS298 Proposal discussion and approval
To Do
- Continue working on Android application to capture frames
CS297
Week 11 : Dec 2- Dec 8
Minutes
- Final Report Submission and CS297 guidelines
- Possible Improvements in the CS297 Report
- CS298 initial plan
To Do
- Validate website with required guidelines
Week 10 : Nov 24- Dec 2
Minutes
- Deployed tflite model on android application for initial testing
- Evaluated CS297 final report and discussed about possible improvements
To Do
Week 9 : Nov 11- Nov 24
Minutes
- Delivered Android Application that can access both cameras simultaneously (Deliverable 3)
- Initial Discussion about Deliverable 4
- Discussed about converting Keras model to tfite model
To Do
- Deliverable 4
- Converted trite model to deploy on android application
Week 8 : Nov 11- Nov 18
Minutes
- Delivered Initial Android Application
- Discussed about further scope of Deliverable 3
To Do
Week 7 : Nov 4- Nov 11
Minutes
- Submitted Deliverable 2 with 51 Videos Dataset
- Improvements in Unity Video Using Camera Move
- Discussed about Deliverable 3
To Do
- Deliverable 2
- Initial phase of Deliverable 3
Week 6 : Oct 27- Nov 4
Minutes
- Delivered Initial Video of Facial Expression Generated by Unity
- Discussed Changes to make it better
To Do
- Deliverable 2
- Improvement in Video
Week 5 : Oct 20- Oct 27
Minutes
- Delivered a basic unity facial expression model
- Discussed Unity to generate dataset to change expressions
To Do
- Deliverable 2
- Presentation on Unity Basics
Week 4 : Oct 13- Oct 20
Minutes
- Delivered depth wise sequential model
- Delivered first deliverable
- Discussed Unity to generate dataset
To Do
- Do a Tutorial on Unity
- Initial Unity Model to show one expression
Week 3 : Oct 6- Oct 13
Minutes
- First Paper Presentation. Paper Name : "Research of Facial Expression Recognition Based on Deep Learning"
- Finalized the Sequential Model
- Discussed about Depth wise sequential model described in the paper and its advantages
To Do
- Design of Depth wise sequential model for my application
Week 2 : Sept 29- Oct 6
Minutes
- Discussed about the FerNET2013 Dataset. Categorized the Expressions in 7 classes
- Discussed the accuracy of initial sequential Model
To Do
- First Paper Presentation
- Parameter Tuning in Sequential Model
Week 1 : Sept 23- Sept 29
Minutes
- Kickoff meeting and Idea Discussion
- Finalized the Proposal
To Do
- Finalizing the Sample Dataset
- Image Preprocessing
- Design initial Sequential Model
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