Related papers: Write error rate of spin-transfer-torque random ac…

This paper deals with the problem of remote estimation of the state of a discrete-time stochastic linear system observed by a sensor with computational capacity to calculate local estimates. We design an event-triggered communication (ETC)…

Code-switching, the alternation of languages within a single discourse, presents a significant challenge for Automatic Speech Recognition. Despite the unique nature of the task, performance is commonly measured with established metrics such…

In this manuscript we continue the thread of [M. Chertkov, F. Pan, M. Stepanov, Predicting Failures in Power Grids: The Case of Static Overloads, IEEE Smart Grid 2011] and suggest a new algorithm discovering most probable extreme stochastic…

The discovery of spin-orbit torques (SOTs) generated through the spin Hall or Rashba effects provides an alternative write approach for magnetic random-access memory (MRAM), igniting the development of spin-orbitronics in recent years.…

There is an extremely high demand for a high speed, low power, low leakage, and low noise Static Random-Access Memory (SRAM) for high performance cache memories. The energy efficiency of SRAM is of paramount importance in both high…

A model of superconducting computer memory exploiting the orthogonal spin transfer (OST) in the pseudospin valve (PS) that is controlled by the three-terminal Josephson superconducting-ferromagnetic transistor (SFT) is developed. The…

We study the problem of evaluating automatic speech recognition (ASR) systems that target dialectal speech input. A major challenge in this case is that the orthography of dialects is typically not standardized. From an ASR evaluation…

This paper investigates the impact of thermal stability relaxation in double-barrier magnetic tunnel junctions (DMTJs) for energy-efficient spin-transfer torque magnetic random access memories (STT-MRAMs) operating at the liquid nitrogen…

Text encodings from automatic speech recognition (ASR) transcripts and audio representations have shown promise in speech emotion recognition (SER) ever since. Yet, it is challenging to explain the effect of each information stream on the…

The speed of writing of state-of-the-art ferromagnetic memories is physically limited by an intrinsic GHz threshold. Recently, an alternative research direction has been initiated by realizing memory devices based on antiferromagnets in…

Automatic Speech Recognition (ASR) plays a crucial role in human-machine interaction and serves as an interface for a wide range of applications. Traditionally, ASR performance has been evaluated using Word Error Rate (WER), a metric that…

Many studies have examined the shortcomings of word error rate (WER) as an evaluation metric for automatic speech recognition (ASR) systems. Since WER considers only literal word-level correctness, new evaluation metrics based on semantic…

In this letter, we show that Giant Spin Hall Effect (GSHE) MRAM can enable better energy- delay and voltage performance than traditional MTJ based spin torque devices at scaled nanomagnet dimensions (10-30 nm). Firstly, we derive the effect…

In this paper, we present a Small Energy Masking (SEM) algorithm, which masks inputs having values below a certain threshold. More specifically, a time-frequency bin is masked if the filterbank energy in this bin is less than a certain…

We investigate fast-pulse switching of in-plane-magnetized magnetic tunnel junctions (MTJs) within 3-terminal devices in which spin-transfer torque is applied to the MTJ by the giant spin Hall effect. We measure reliable switching, with…

Transfer learning from high-resource languages is known to be an efficient way to improve end-to-end automatic speech recognition (ASR) for low-resource languages. Pre-trained or jointly trained encoder-decoder models, however, do not share…

We propose a lightweight scheme where the formation of a data block is changed in such a way that it can tolerate soft errors significantly better than the baseline. The key insight behind our work is that CNN weights are normalized between…

In a wide range of statistical learning problems such as ranking, clustering or metric learning among others, the risk is accurately estimated by $U$-statistics of degree $d\geq 1$, i.e. functionals of the training data with low variance…

The spin torque assisted thermal switching of the single free layer was studied theoretically. Based on the rate equation, we derived the theoretical formulas of the most likely and mean switching currents of the sweep current assisted…

We realized an organic electrical memory device with a simple structure based on single layer pentacene film embedded between Al and ITO electrodes. The optimization of the thickness and deposition rate of pentacene resulted in a reliable…