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X-ORIGINAL-URL:https://ece.hku.hk
X-WR-CALDESC:Events for Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
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TZID:Asia/Hong_Kong
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DTSTART:20230101T000000
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DTSTART;TZID=Asia/Hong_Kong:20241129T100000
DTEND;TZID=Asia/Hong_Kong:20241129T110000
DTSTAMP:20260512T115009
CREATED:20241125T025653Z
LAST-MODIFIED:20250114T031324Z
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SUMMARY:RPG Seminar – Wireless Sensing for Speech Recovery and Recognition
DESCRIPTION:Abstract\nConsidering the microphone is easily affected by noise and soundproof materials\, the radio frequency (RF) signal is a promising candidate to recover audio as it is immune to noise and can traverse many soundproof objects. We introduce Radio2Speech\, a system that uses RF signals to recover high quality speech from the loudspeaker. Radio2Speech can recover speech comparable to the quality of the microphone\, advancing from recovering only single tone music or incomprehensible speech in existing approaches. Quantitative and qualitative evaluations show that in quiet\, noisy and soundproof scenarios\, Radio2Speech achieves state-of-the-art performance and is on par with the microphone that works in quiet scenarios. Moreover\, millimeter wave (mmWave) based speech recognition provides more possibility for audio-related applications\, such as conference speech transcription and eavesdropping. However\, considering the practicality in real scenarios\, latency and recognizable vocabulary size are two critical factors that cannot be overlooked. We also propose Radio2Text\, the first mmWave-based system for streaming automatic speech recognition (ASR) with a vocabulary size exceeding 13\,000 words. The experimental results show that our Radio2Text can achieve a character error rate of 5.7% and a word error rate of 9.4% for the recognition of a vocabulary consisting of over 13\,000 words. \nSpeaker\nMr. Zhao Running\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the speaker\nRunning Zhao is pursuing the Ph.D. degree with the Department of Electrical and Electronic Engineering at the University of Hong Kong\, and he is advised by Edith C.H. Ngai. He received the B.S. and M.S. degree from Wuhan University of Technology\, Wuhan\, China\, in 2018 and 2021. His current research interests include human-computer interaction\, ubiquitous computing\, and multimodal learning\, with a particular emphasis on using different modalities or sensors to investigate applications for HCI and healthcare. \nOrganizer\nProf. Edith C.H. Ngai \nAll are welcome.
URL:https://ece.hku.hk/events/20241129-1/
LOCATION:Online via Zoom
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/11/rpg-seminar.jpg
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DTSTART;TZID=Asia/Hong_Kong:20241129T150000
DTEND;TZID=Asia/Hong_Kong:20241129T160000
DTSTAMP:20260512T115009
CREATED:20241125T025933Z
LAST-MODIFIED:20250114T031215Z
UID:19465-1732892400-1732896000@ece.hku.hk
SUMMARY:RPG Seminar – Discrimination of Developmental Trajectories in Brain Structural Features of ASD
DESCRIPTION:Zoom ID: 998 6183 8733\nPassword: 275656 \nAbstract\nAutism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by challenges in social interaction\, communication\, and repetitive behaviors. Structural brain abnormalities associated with ASD are known to evolve across the developmental trajectory\, making it difficult to identify consistent biomarkers for accurate individual diagnosis. In this seminar\, we explore age-related variations in cortical thickness (CT) and gray matter volume (GMV) using a novel Partial Least Squares (PLS)-based method combined with feature selection techniques. Key findings reveal significant developmental abnormalities in several brain regions\, which were strongly correlated with behavioral measures such as Autism Diagnostic Observation Schedule (ADOS) scores. The incorporation of age-related features not only enhanced classification accuracy but also provided new insights into the developmental and behavioral mechanisms underlying ASD. These results highlight the critical role of age in understanding ASD and improving diagnostic and therapeutic strategies. \nSpeaker\nMs. Guo Zifan\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the speaker\nZifan Guo received the B.S. degree from the University of Electronic Science and Technology of China\, Chengdu\, China\, in 2021. She is pursuing the Ph.D. degree with the Department of Electrical and Electronic Engineering at the University of Hong Kong\, Hong Kong. \nOrganizer\nProf. S. C. Chan \nAll are welcome.
URL:https://ece.hku.hk/events/20241129-2/
LOCATION:Online via Zoom
CATEGORIES:Seminar
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