Michael Xuelin Huang

schoolSaarland Informatics Campusbar_chart#1410 Global Rank

Total Papers

HCI Rank

#1410

Research Areas

Years Active

Recent Publications

Tap&Say: Touch Location-Informed Large Language Model for Multimodal Text Correction on Smartphones

While voice input offers a convenient alternative to traditional text editing on mobile devices, practical implementations face two key challenges: 1) reliably distinguishing between editing commands and content dictation, and 2) effortlessly pinpointing the intended edit location. We propose Tap&Say, a novel multimod…

CHI '245th+ AuthorVoice User Interface (VUI) Design +2

Rambler: Supporting Writing With Speech via LLM-Assisted Gist Manipulation

Dictation enables efficient text input on mobile devices. However, writing with speech can produce disfluent, wordy, and incoherent text and thus requires heavy post-processing. This paper presents Rambler, an LLM-powered graphical user interface that supports gist-level manipulation of dictated text with two main set…

CHI '211st AuthorFoot & Wrist Interaction +1

TapNet: The Design, Training, Implementation, and Applications of a Multi-Task Learning CNN for Off-Screen Mobile Input

To make off-screen interaction without specialized hardware practical, we investigate using deep learning methods to process the common built-in IMU sensor (accelerometers and gyroscopes) on mobile phones into a useful set of one-handed interaction events. We present the design, training, implementation and applicat…

CHI '20CorrespondingIn-Vehicle Haptic, Audio & Multimodal Feedback +1

WATouCH: Enabling Direct Input on Non-touchscreen Using Smartwatch's Photoplethysmogram and IMU Sensor Fusion

Interacting with non-touchscreens such as TV or public displays can be difficult and inefficient. We propose WATouCH, a novel method that localizes a smartwatch on a display and allows direct input by turning the smartwatch into a tangible controller. This low-cost solution leverages sensor fusion of the built-in iner…

IUI '182nd AuthorEye Tracking & Gaze Interaction +1

Detecting low rapport during natural interactions in small groups from non-verbal behavior

Rapport, the close and harmonious relationship in which interaction partners are “in sync” with each other, was shown to result in smoother social interactions, improved collaboration, and improved interpersonal outcomes. In this work, we are first to investigate automatic prediction of low rapport during natural inte…

IUI '184th AuthorHuman Pose & Activity Recognition +1

Ev’ry Little Movement Has a Meaning of Its Own: Using Past Mouse Movements to Predict the Next Interaction

User experience could be enhanced if the computer could understand human interaction intention. For instance, it could react to intercept and prevent interaction errors. This paper presents an approach to predicting users’ intention in interaction tasks based on past mouse movements. We adopt a long short-term memory…

CHI '182nd AuthorEye Tracking & Gaze Interaction +1

Training Person-Specific Gaze Estimators from User Interactions with Multiple Devices

Learning-based gaze estimation has significant potential to enable attentive user interfaces and gaze-based interaction on the billions of camera-equipped handheld devices and ambient displays. While training accurate person- and device-independent gaze estimators remains challenging, person-specific training is feasi…

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