Learning is a game and group project is a good learning game.
The goal of this group project is to encourage students to explore DSP techniques to understand advanced applications in daily life.
Students need to form a project team with 3 members to complete a DSP-related project.
The project can analyze/evaluate/compare existing DSP technologies through literature surveys, and then implement related DSP algorithms in Colab using Python.
Group Project Assessment:
Project Proposal (Week 5)
A 2-page project proposal with motivation, DSP topic and implementation plan.
Submit the project proposal in PDF format to CANVAS proposal assignment.
Proposal must contain:
Project Title
Student Name, Student ID and Email Address of each member
Summary with goals of the project in about 300 words. The detail description of the project and the work to be carried out in about 1000 words.
References
No more than two groups perform the same or very similar projects
Identical or similar projects may be rejected due to late submission of project proposal
Students are encouraged to submit the project title and short description to the instructor via email (eelmpo@cityu.edu.hk) for approval of the group project title.
Deadline: 27th Sep. 2022
Oral Presentation (Week 12 and 13)
Every group is also required to make a 10-minute Power Point presentation of their term project to the entire class.
The presentation must include:
A short description of the project and its objectives
An explanation of the implemented algorithm and relevant theory
A demonstration of the implemented DSP applicaiton in Colab
Final Report and Source Code (Week 14)
A final report of at least 30 pages.
Suggested structure of the final report:
Abstract, Introduction, Literature Survey, Theory, Implementation, Experimental Results, Conclusion, and References.
Students are also required to submit the Python source code of any implementation and PPT of the oral presentation for assessment.
All the PPT, Final Report and Source Code are required to submit to CANVAS Group Project Final Report
Deadline: 29th Nov 2022
Project Directions
Your passion is your compass.
Something you are interested in or that may help your work or research
Don’t need to develop something original, but should
Read and describe relevant papers in literature
Do some applications of relevant techniques
Could investigate something we have covered briefly, or that is related to some topics in the course.
The following are some suggested DSP topics suitable for the group project:
Remind students that these are only suggested topics for your preliminary research to determine your project.
Students are encouraged trying to come up with your own project idea.
Presentation Schedule:
Section A (Week 12)
Group 1 : Noise Reduction for Audio Processing
Zhang Yi Fan, Chan King Yim, Lee Marcus Owen, Zhou Xiyao
Group 2 : Audio Classification using Deep Learning
HUANG Yixiao, CHEN Bo-Han, LIU Yuxi
Group 3 : DSP-based Preprocessing of Arm's EMG Signal for LSTM Hand Gesture Recognition
LI Jiaxing, MENG Fanqi, YANG Yiming
Group 4 : Generating Piano Music with Dilated Convolutional Neural Networks
ZHANG Keyang, LI Fengjuan, MA Haoxuan
Group 5 : Noise Cancelling Headphones
Lo Wai Yu Elanor, Leung Hoi Tung, Fung Hoi Lam, Lee Kiu Chi
Group 6 : Generating Melodies with LSTM
Chu Kwun Cheung, Chan Kam Tai Kevin, Lam Chun
Section B (Week 13)
Group 7 : Speech Recognition With Python
JI Haoran, WANG Haobo, ZHANG Tingkai
Group 8 : Sound Classification Using Deep Learning
LEI Sheng, PENG Yang, LIU Yuyang
Group 9 : Text to Speech in Python
Lam Chi Hok, Lau Owen, Chow Ngai Long
Group 10 : Generating Music through Deep Learning
Yussif BAMIE MUBASHIR, SIT Chun Yin, CHEUK SHUN SHING, Russell, Yeung Man Hin
Group 11 : Audio Classification
Cheung Ka Tsun, THANOMSAKYUTH Bhurin, Ho Wai Lat, Cheng Ki Chung
Group 12 : Audio Genre Classification with Python OOP
Wong Tsz Hung, Wong Ho Kin, Woo Sangwon
Group 13 : Audio Equalizer
Wong Ho San, Ngan Wai Sing, Cheng Ki Fung, CHAN Tsz Hong
