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In human-machine systems (HMS), trust placed by humans on machines is a complex concept and attracts increasingly research efforts. Herein, we reviewed recent studies on building and measuring trust in HMS. The review was based on one comprehensive model of trust – IMPACTS, which has 7 features of intention, measurability, performance, adaptivity, communication, transparency, and security. The review found that, in the past 5 years, HMS fulfill the features of intention, measurability, communication, and transparency. Most of the HMS consider the feature of performance.
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- Read more about Estimation of Fields Using Binary Measurements From a Mobile Agent
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- Read more about Improving a User's Haptic Perceptual Sensitivity by Optimizing Effective Manipulability of a Redundant User Interface
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Human perceptual sensitivity of various types of forces, e.g., stiffness and friction, is important for surgeons during robotic surgeries such as needle insertion and palpation. However, force feedback from robot end-effector is usually a combination of desired and undesired force components which could have an effect on the perceptual sensitivity of the desired one. In presence of undesired forces, to improve perceptual sensitivity of desired force could benefit robotic surgical outcomes.
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- Read more about Generating Human Readable Transcript for Automatic Speech Recognition with Pre-trained Language Model
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Modern Automatic Speech Recognition (ASR) systems can achieve high performance in terms of recognition accuracy. However, a perfectly accurate transcript still can be challenging to read due to disfluency, filter words, and other errata common in spoken communication. Many downstream tasks and human readers rely on the output of the ASR system; therefore, errors introduced by the speaker and ASR system alike will be propagated to the next task in the pipeline.
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- Read more about Assisted Learning: Cooperative AI with Autonomy
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In this paper, we propose a method to estimate the proximity of an acoustic reflector, e.g., a wall, using ego-noise, i.e., the noise produced by the moving parts of a listening robot. This is achieved by estimating the times of arrival of acoustic echoes reflected from the surface. Simulated experiments show that the proposed non-intrusive approach is capable of accurately estimating the distance of a reflector up to 1 meter and outperforms a previously proposed intrusive approach under loud ego-noise conditions.
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- Read more about A PARALLELIZABLE LATTICE RESCORING STRATEGY WITH NEURAL LANGUAGE MODELS
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This paper proposes a parallel computation strategy and a posterior-based lattice expansion algorithm for efficient lattice rescoring with neural language models (LMs) for automatic speech recognition. First, lattices from first-pass decoding are expanded by the proposed posterior-based lattice expansion algorithm. Second, each expanded lattice is converted into a minimal list of hypotheses that covers every arc. Each hypothesis is constrained to be the best path for at least one arc it includes.
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- Read more about Federated Learning With Local Differential Privacy: Trade-Offs Between Privacy, Utility, and Communication
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Federated learning (FL) allows to train a massive amount of data privately due to its decentralized structure. Stochastic gradient descent (SGD) is commonly used for FL due to its good empirical performance, but sensitive user information can still be inferred from weight updates shared during FL iterations. We consider Gaussian mechanisms to preserve local differential privacy (LDP) of user data in the FL model with SGD. The trade-offs between user privacy, global utility, and transmission rate are proved by defining appropriate metrics for FL with LDP.
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- Read more about NISP: A Multi-lingual Multi-accent Dataset for Speaker Profiling
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Many commercial and forensic applications of speech demand the extraction of information about the speaker characteristics, which falls into the broad category of speaker profiling. The speaker characteristics needed for profiling include physical traits of the speaker like height, age, and gender of the speaker along with the native language of the speaker. Many of the datasets available have only partial information for speaker profiling.
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