Project overview
This self-initiated undergraduate research explored IoT, machine learning, and voice-based systems for intelligent sensing and interaction, including voice denoising. The title on this page is descriptive; an official project title has not been supplied.
This is one experience, referenced through the Undergraduate Research Opportunities Programme (UROP), Undergraduate Research Experience (UREx) CDE2605R, and the earlier “IoT Voice Denoising” entry. The existing URL is retained so previous links continue to work.
Context
NUS College of Design and Engineering · Undergraduate Researcher
August 2025 – May 2026
Supervised by Dr Rajesh C. Panicker and Professor Biplab Sikdar.
Project supported by a S$2,500 grant.
The work considered how embedded sensing, data-driven models, and voice-based interfaces could be combined in practical engineering applications. Funding describes project support, not a separate personal award.
Objectives and problem statement
The documented scope was to investigate relevant technologies, system architectures, and possible implementation approaches. The precise research question, device constraints, noise conditions, and evaluation objectives still need to be added from the original project materials. Voice denoising and voice recognition are related parts of this account, not interchangeable tasks.
Individual responsibilities
- Reviewed relevant literature and technologies.
- Investigated IoT, machine learning, and voice recognition in an applied engineering context.
- Explored system architectures and implementation approaches.
- Contributed to planning, technical exploration, and prototype development.
- Undertook experimentation, troubleshooting, documentation, and discussions with supervisors.
The exact ownership of individual deliverables remains to be documented. These activities do not imply a completed or deployed system.
Approach and development process
The available record supports literature review, architecture exploration, experimentation, prototyping, and iterative troubleshooting. A chronological account of design decisions and experiments will be added from the project records.
Technical details pending: algorithms, datasets, hardware, software frameworks, implementation constraints, and evaluation protocol. No particular method or tool is claimed without documentation.
Documented outcomes
The research period ended in May 2026. The supplied record describes participation in the research process and prototype development; it does not establish a final prototype status, quantitative performance improvement, deployment, or publication.
No measured results have been supplied. The cover waveform is conceptual, not experimental data.
Visual materials
Project photographs, verified architecture diagrams, and any demonstration will be added when available and cleared for sharing. The original conceptual illustration remains labelled as a placeholder.
Challenges and lessons
The experience involved research problem formulation, engineering design, documentation, and interdisciplinary thinking. Specific technical challenges, failed approaches, and lessons need to be grounded in the original notes before they are described here.
Research materials
Reports, posters, technical demonstrations, publications if any become available, and project-specific repositories can be linked through the Research page. No public output has been supplied yet.
项目概述
这项自主选题的本科研究探索物联网、机器学习与面向智能感知和交互的语音系统，包括语音降噪。本页使用描述性标题，正式项目名称尚未提供。
本科生研究机会项目（UROP）、本科生研究体验（UREx）CDE2605R 与此前的“物联网语音降噪”条目指向同一项经历。原有网址予以保留，确保旧链接继续有效。
背景
新加坡国立大学设计与工程学院 · 本科生研究参与者
2025 年 8 月—2026 年 5 月
指导：Rajesh C. Panicker 博士、Biplab Sikdar 教授。
项目获 S$2,500 经费支持。
研究关注嵌入式感知、数据驱动模型与语音接口如何结合，以支持实际工程应用。经费信息描述项目支持，并非另一项个人奖项。
目标与问题定义
已记录的范围包括调查相关技术、系统架构和可能的实现途径。具体研究问题、设备约束、噪声条件与评估目标，仍需根据原始项目资料补充。语音降噪与语音识别是本研究叙述中相关但不同的任务，不作混同。
个人职责
- 阅读相关文献并调查技术。
- 在应用工程背景下探索物联网、机器学习与语音识别。
- 调查系统架构与实现途径。
- 参与规划、技术探索与原型开发。
- 参与实验、故障排查、文档整理及导师讨论。
具体交付成果的个人分工仍待整理。参与这些活动不意味着系统已完成或部署。
方法与开发过程
现有记录支持文献综述、架构探索、实验、原型开发和迭代排查等活动。设计决策与实验的时间线将在整理原始资料后补充。
**技术细节待补充：**算法、数据集、硬件、软件框架、实现约束与评估流程。缺乏记录时，不声称采用了某种具体方法或工具。
已记录的结果
研究时间截至 2026 年 5 月。现有资料描述了研究过程与原型开发中的参与，但并未确认最终原型状态、量化性能改善、部署或论文发表。
目前未提供测量结果。封面波形为概念示意，并非实验数据。
视觉资料
项目照片、经过核实的架构图与演示，将在资料齐备并获准公开后添加。原有概念插图继续明确标注为占位内容。
挑战与反思
这段经历涉及研究问题界定、工程设计、文档整理与跨学科思考。具体技术困难、未成功的方法及相应反思，需要依据原始笔记再作叙述。
研究资料
报告、海报、技术演示、未来如有的论文，以及项目专属代码仓库，可通过研究页面添加链接。目前尚未提供可公开的研究产出。