Publications associées à HMM-Based Error Correction Mechanism for Five-Key Chording Keyboards

Publications associées (25)

Ultrahigh Electrostrictive Effect in Lead-Free Ferroelectric Ceramics Via Texture Engineering

The electrostrictive effect, which induces strain in ferroelectric ceramics, offers distinct advantages over its piezoelectric counterpart for high-precision actuator applications, including anhysteretic behavior even at high frequencies, rapid reaction ti ...

Amer Chemical Soc2023

Critical Schrodinger Cat Qubit

Vincenzo Savona, Fabrizio Minganti, Luca Gravina

Encoding quantum information onto bosonic systems is a promising route to quantum error correc-tion. In a cat code, this encoding relies on the confinement of the dynamics of the system onto the two-dimensional manifold spanned by Schrodinger cats of oppos ...

AMER PHYSICAL SOC2023

Hidden Markov Modeling Over Graphs

Ali H. Sayed, Stefan Vlaski, Virginia Bordignon, Mert Kayaalp

This work proposes a multi-agent filtering algorithm over graphs for finite-state hidden Markov models (HMMs), which can be used for sequential state estimation or for tracking opinion formation over dynamic social networks. We show that the difference fro ...

IEEE2022

A note on universal inference

Anthony Christopher Davison, Timmy Rong Tian Tse

Universal inference enables the construction of confidence intervals and tests without regularity conditions by splitting the data into two parts and appealing to Markov's inequality. Previous investigations have shown that the cost of this generality is a ...

WILEY2022

Predicting learners' effortful behaviour in adaptive assessment using multimodal data

Kshitij Sharma, Jennifer Kaitlyn Olsen

Many factors influence learners' performance on an activity beyond the knowledge required. Learners' on-task effort has been acknowledged for strongly relating to their educational outcomes, reflecting how actively they are engaged in that activity. Howeve ...

ASSOC COMPUTING MACHINERY2020

Coded LoRa Frame Error Rate Analysis

Andreas Peter Burg, Alexios Konstantinos Balatsoukas Stimming, Orion Afisiadis

In this work, we study the coded frame error rate (FER) of LoRa under additive white Gaussian noise (AWGN) and under carrier frequency offset (CFO). To this end, we use existing approximations for the bit error rate (BER) of the LoRa modulation under AWGN ...

IEEE2020

On quantifying the quality of acoustic models in hybrid DNN-HMM ASR

Hervé Bourlard, Afsaneh Asaei, Pranay Dighe

We propose an information theoretic framework for quantitative assessment of acoustic models used in hidden Markov model (HMM) based automatic speech recognition (ASR). The HMM backend expects that (i) the acoustic model yields accurate state conditional e ...

ELSEVIER2020

Kramers Kronig detection of four 20 Gbaud 16-QAM channels using Kerr combs for a shared phase estimation

Tobias Kippenberg, Maxim Karpov, Martin Hubert Peter Pfeiffer, Arne Kordts, Fatemeh Alishahi

We experimentally demonstrate Kramers-Kronig detection of four 20 Gbaud 16-quadrature-amplitude-modulated (QAM) channels after 50 km fiber transmission using two soliton Kerr combs as signal sources and local oscillators. The estimated carrier phase at the ...

OPTICAL SOC AMER2020

A 161-mW 56-Gb/s ADC-Based Discrete Multitone Wireline Receiver Data-Path in 14-nm FinFET

Yusuf Leblebici, Andreas Peter Burg, Alessandro Cevrero, Thomas Toifl, Lukas Kull, Ilter Ozkaya, Gain Kim, Cosimo Aprile

This article introduces a wireline receiver (RX) data-path employing discrete multi-tone (DMT) modulation for communicating over electrical links. The DMT RX incorporates a fully digital equalization data-path, with a synthesized and automatically placed a ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Multilingual Training and Adaptation in Speech Recognition

Sibo Tong

State-of-the-art acoustic models for Automatic Speech Recognition (ASR) are based on Hidden Markov Models (HMM) and Deep Neural Networks (DNN) and often require thousands of hours of transcribed speech data during training. Therefore, building multilingual ...

EPFL2020

Gaussian channel transmission of images and audio files using cryptcoding

Random codes based on quasigroups (RCBQ) are cryptcodes, i.e. they are error-correcting codes, which provide information security. Cut-Decoding and 4-Sets-Cut-Decoding algorithms for these codes are defined elsewhere. Also, the performance of these codes f ...

2019

Impact of Memory Voltage Scaling on Accuracy and Resilience of Deep Learning Based Edge Devices

David Atienza Alonso, Andreas Peter Burg, Miguel Peon Quiros, Martino Ruggiero, Andrea Bonetti, Flavio Ponzina, Benoît Walter Denkinger, Soumya Subhra Basu, Szabolcs Balási

Energy consumption is a significant obstacle to integrate deep learning into edge devices. Two common techniques to curve it are quantization, which reduces the size of the memories (static energy) and the number of accesses (dynamic energy), and voltage s ...

2020

Experimental demonstration of three-fold wavelength multicasting of a 64-QAM 120 Gbit/s data channel using a Kerr frequency comb and nonlinear wave mixing

Tobias Kippenberg, Maxim Karpov, Martin Hubert Peter Pfeiffer, Arne Kordts, Fatemeh Alishahi

We experimentally demonstrate three-fold wavelength multicasting of a 64-quadrature-amplitude-modulation (QAM), 120-Gbit/s data channel using a microresonator Kerr frequency comb and nonlinear wave mixing. The multicasting is achieved with a data signal an ...

SPIE-INT SOC OPTICAL ENGINEERING2019

Multigrid Methods Combined With Low-Rank Approximation For Tensor-Structured Markov Chains

Daniel Kressner, Francisco Santos Paredes Quartin de Macedo

Markov chains that describe interacting subsystems suffer from state space explosion but lead to highly structured matrices. In this work, we propose a novel tensor-based algorithm to address such tensor-structured Markov chains. Our algorithm combines a t ...

2018

Low-rank tensor methods for large Markov chains and forward feature selection methods

Francisco Santos Paredes Quartin de Macedo

In the first part of this thesis, we present and compare several approaches for the determination of the steady-state of large-scale Markov chains with an underlying low-rank tensor structure. Such structure is, in our context of interest, associated with ...

EPFL2018

Efficient Learning from Comparisons

Lucas Maystre

Humans are comparison machines: comparing and choosing an item among a set of alternatives (such as objects or concepts) is arguably one of the most natural ways for us to express our preferences and opinions. In many applications, the analysis of data con ...

EPFL2018

Effects of erbium-doped fiber amplifier induced pump noise on soliton Kerr frequency combs for 64-quadrature amplitude modulation transmission

Tobias Kippenberg, Maxim Karpov, Martin Hubert Peter Pfeiffer, Arne Kordts, Fatemeh Alishahi

We experimentally investigate the effects of erbium-doped fiber amplifier induced pump noise on soliton Kerr frequency combs for 64-quadrature amplitude modulation (QAM) transmission. We find that the optical carrier-to-noise ratios (OCNRs) of the comb lin ...

2018

Low-rank and Sparse Soft Targets to Learn Better DNN Acoustic Models

Hervé Bourlard, Afsaneh Asaei, Pranay Dighe

Conventional deep neural networks (DNN) for speech acoustic modeling rely on Gaussian mixture models (GMM) and hidden Markov model (HMM) to obtain binary class labels as the targets for DNN training. Subword classes in speech recognition systems correspond ...

Ieee2017

Learning Stable Task Sequences from Demonstration with Linear Parameter Varying Systems and Hidden Markov Models

Aude Billard

The problem of acquiring multiple tasks from demonstration is typi- cally divided in two sequential processes: (1) the segmentation or identification of different subgoals/subtasks and (2) a separate learning process that parameterizes a control policy for ...

robot-learning2017

High-Speed Wireline Link Design

Hazar Yüksel

High-speed serial links are a crucial application of semiconductor technology and have been the enabler of the scaling of computing systems. The increasing data-rate requirements of these links have only been partially satisfied by advancements in process ...

EPFL2017