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Integrating spatial context into large language models (LLMs) has the potential to revolutionize human-computer interaction, particularly in wearable devices. In this work, we present a novel system architecture that incorporates spatial speech understanding into LLMs, enabling contextually aware and adaptive applications for wearable technologies. Our approach leverages microstructure-based spatial sensing to extract precise Direction of Arrival (DoA) information using a monaural microphone. To address the lack of existing dataset for microstructure-assisted speech recordings, we synthetically create a dataset called OmniTalk by using the LibriSpeech dataset. This spatial information is fused with linguistic embeddings from OpenAI’s Whisper model, allowing each modality to learn complementary contextual representations. The fused embeddings are aligned with the input space of LLaMA-3.2 3B model and fine-tuned with lightweight adaptation technique LoRA to optimize for on-device processing. 

A finite element model consisting of a conducting filament with or without a gap was used to reproduce the behavior of TaOx-based resistive switching devices. The specific goal was to explore the range of possible filament parameters such as filament diameter, composition, gap width, and composition to reproduce the conductance and shape of I–V while keeping the maximum temperature within the acceptable range allowing for ion motion and preventing melting. The model solving heat and charge transport produced a good agreement with experimental data for the oxygen content in the filament below TaO1.3, the filament diameter range between 6 and 22 nm, and the gap oxygen content between TaO1.7 and TaO1.85. Gap width was not limited to either low or high sides according to the criteria considered in this report. The obtained filament composition corresponds to oxygen deficiency an order of magnitude higher than one estimated by other modeling efforts. This was in large part due to the use of recent experimental values of conductivity as a function of composition and temperature. Our modeling results imply that a large fraction of atoms leaves and/or accumulates within the filament to produce a large relative concentration change. This, in turn, necessitates the inclusion of strain energy in the filament formation modeling. In addition, the results reproduce non-linear I–V without the necessity of assuming the Poole–Frenkel type of electrical conduction or the presence of a barrier at the oxide/metal interface. 

This paper presents the design and implementation of Scribe, a comprehensive voice processing and handwriting interface for voice assistants. Distinct from prior works, Scribe is a precise tracking interface that can co-exist with the voice interface on low sampling rate voice assistants. Scribe can be used for 3D free-form drawing, writing, and motion tracking for gaming. Taking handwriting as a specific application, it can also capture natural strokes and the individualized style of writing while occupying only a single frequency. The core technique includes an accurate acoustic ranging method called Cross Frequency Continuous Wave (CFCW) sonar, enabling voice assistants to use ultrasound as a ranging signal while using the regular microphone system of voice assistants as a receiver. We also design a new optimization algorithm that only requires a single frequency for time difference of arrival. Scribe prototype achieves 73 μm of median error for 1D ranging and 1.4 mm of median error in 3D tracking of an acoustic beacon using the microphone array used in voice assistants. Our implementation of an in-air handwriting interface achieves 94.1% accuracy with automatic handwriting-to-text software, similar to writing on paper (96.6%). At the same time, the error rate of voice-based user authentication only increases from 6.26% to 8.28%. 

Abstract Some of the most astonishing and prominent properties of Quantum Mechanics, such as entanglement and Bell nonlocality, have only been studied extensively in dedicated low-energy laboratory setups. The feasibility of these studies in the high-energy regime explored by particle colliders was only recently shown and has gathered the attention of the scientific community. For the range of particles and fundamental interactions involved, particle colliders provide a novel environment where quantum information theory can be probed, with energies exceeding by about 12 orders of magnitude those employed in dedicated laboratory setups. Furthermore, collider detectors have inherent advantages in performing certain quantum information measurements and allow for the reconstruction of the state of the system under consideration via quantum state tomography. Here, we elaborate on the potential, challenges, and goals of this innovative and rapidly evolving line of research and discuss its expected impact on both quantum information theory and high-energy physics.