This project aims to develop an intelligent active noise control (ANC) system for electric vehicles (EVs), integrating sound source visualization techniques with deep neural network (DNN) algorithms to enhance cabin acoustic quality and anomaly detection capabilities.

The real-time ANC mechanisms, enabling the system to generate counter-phase signals while preserving speech intelligibility. A modular system architecture will be developed comprising sound field visualization, sound source separation, deep learning based audio signal processing, human-machine interface design, and embedded system integration.

Start Date: Flexible (to be determined based on the selected candidates)

Eligibility: The project is open to up to 2 undergraduate students

Skills and Knowledge Required: Familiar with Python and deep learning frameworks, with a strong emphasis on solid theoretical foundations, particularly in mathematics and mechanics.

Financial Support: Up to 15,000 TWD per month (approximately 450 USD).

Application Process: Interested applicants should submit:

1. A resume or CV detailing relevant skills and experience

2. A cover letter expressing interest and motivation for the project

3. Transcripts (for students)

How to Apply: Please send your application to yjlee@stust.edu.tw with the subject line: “TEEP Project_(Your Name)”. We look forward to receiving your application. (Structural Dynamics and Vibration Laboratory)