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Acoustic monitoring has recently shown great potential in the diagnosis of infrastructure condition. However, due to the severe noise interference in acoustic signals, meaningful features tend to be difficult to infer. It creates a…
Aerospace engines, as critical components in aviation and aerospace industries, require continuous and accurate fault diagnosis to ensure operational safety and prevent catastrophic failures. While deep learning techniques have been…
The high-intensity, repetitive noise associated with functional magnetic resonance imaging hinders on-line monitoring of subjects' speech and/or recording speech signals suitable for off-line analysis. The proposed algorithm enhances the…
Quench diagnostics in superconducting accelerator magnets is essential for understanding performance limitations and improving magnet design. Applicability of the conventional quench diagnostics methods such as voltage taps or quench…
Although general purpose robotic manipulators are becoming more capable at manipulating various objects, their ability to manipulate millimeter-scale objects are usually very limited. On the other hand, ultrasonic levitation devices have…
In the end-of-line test of geared motors, the evaluation of product qual-ity is important. Due to time constraints and the high diversity of variants, acous-tic measurements are more economical than vibration measurements. However, the…
Sound is one of the most informative and abundant modalities in the real world while being robust to sense without contacts by small and cheap sensors that can be placed on mobile devices. Although deep learning is capable of extracting…
Audio fingerprinting (AFP) allows the identification of unknown audio content by extracting compact representations, termed audio fingerprints, that are designed to remain robust against common audio degradations. Neural AFP methods often…
Carrier noise in coherent tones limits sensitivity and causes heating in many experimental systems, such as force sensors, time-keeping, and studies of macroscopic quantum phenomena. Much progress has been made to reduce carrier noise using…
Object transport tasks are fundamental in robotic automation, emphasizing the importance of efficient and secure methods for moving objects. Non-prehensile transport can significantly improve transport efficiency, as it enables handling…
Automatic speech quality assessment aims to quantify subjective human perception of speech through computational models to reduce the need for labor-consuming manual evaluations. While models based on deep learning have achieved progress in…
This study presents a deep-learning framework for controlling multichannel acoustic feedback in audio devices. Traditional digital signal processing methods struggle with convergence when dealing with highly correlated noise such as…
Several studies have been conducted to automatically recognize activities of construction equipment using their generated sound patterns. Most of these studies are focused on single-machine scenarios under controlled environments. However,…
In Physical Human--Robot Interaction (pHRI) grippers, humans and robots may contribute simultaneously to actions, so it is necessary to determine how to combine their commands. Control may be swapped from one to the other within certain…
With computers getting more and more powerful and integrated in our daily lives, the focus is increasingly shifting towards more human-friendly interfaces, making Automatic Speech Recognition (ASR) a central player as the ideal means of…
The perception and recognition of the surroundings is one of the essential tasks for a robot. With preliminary knowledge about a target object, it can perform various manipulation tasks such as rolling motion, palpation, and force control.…
Sensing via a mechanical frequency shift is a powerful measurement tool, and, therefore, understanding and mitigating frequency noise affecting mechanical resonators is imperative. Thermomechanical noise fundamentally limits mechanical…
Contact feedback is essential for contact-rich robotic manipulation, as it allows the robot to detect subtle interaction changes and adjust its actions accordingly. Six-axis force-torque sensors are commonly used to obtain contact feedback,…
Handling fragile objects remains a major challenge for robotic manipulation. Tactile sensing and soft robotics can improve delicate object handling, but typically involve high integration complexity or slow response times. We address these…
Having accurate localization capabilities is one of the fundamental requirements of autonomous robots. For underwater vehicles, the choices for effective localization are limited due to limitations of GPS use in water and poor environmental…