Hyeongjun Choi, Young Eun Kwon, Ji Won Yoon (Korea University)

This paper presents mmProcess, a novel phasebased approach for speech reconstruction using millimeterwave (mmWave) technology, offering an alternative to existing Doppler-based and deep learning-dependent methods. By leveraging the phase variations in mmWave signals, mmProcess enables precise detection of fine vibrations caused by sound, facilitating accurate speech reconstruction without the need for large training datasets, prior knowledge, or complex neural networks. This eliminates the limitations of deep learning approaches, such as degraded performance with unseen languages and the significant time and cost required for system development. mmProcess combines advanced signal processing techniques, including range processing, phase unwrapping, and noise filtering, to transform raw mmWave radar data into high-fidelity speech signals. Experimental evaluations validate the effectiveness of the method, demonstrating its capability to operate in challenging scenarios while maintaining adaptability and cost efficiency.

View More Papers

Can a Cybersecurity Question Answering Assistant Help Change User...

Lea Duesterwald (Carnegie Mellon University), Ian Yang (Carnegie Mellon University), Norman Sadeh (Carnegie Mellon University)

Read More

Work-in-Progress: Towards Browser-Based Consent Management

Gayatri Priyadarsini Kancherla and Abhishek Bichhawat (Indian Institute of Technology Gandhinagar)

Read More

Understanding Miniapp Malware: Identification, Dissection, and Characterization

Yuqing Yang (The Ohio State University), Yue Zhang (Drexel University), Zhiqiang Lin (The Ohio State University)

Read More

Understanding Influences on SMS Phishing Detection: User Behavior, Demographics,...

Daniel Timko (California State University San Marcos), Daniel Hernandez Castillo (California State University San Marcos), Muhammad Lutfor Rahman (California State University San Marcos)

Read More