Concept

Cache language model

Publications associées (20)

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Edoardo Charbon, Claudio Bruschini, Andrei Ardelean, Paul Mos, Yang Lin

Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, ...

Berlin2024

Analysis of Dampers in Time-Sensitive Networks With Non-Ideal Clocks

Jean-Yves Le Boudec, Ehsan Mohammadpour

Dampers are devices that reduce delay jitter in the context of time-sensitive networks, by delaying packets for the amount written in packet headers. Jitter reduction is required by some real-time applications; beyond this, dampers have the potential to so ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Language model domain adaptation for automatic speech recognition

Petr Motlicek, Amrutha Prasad

This report provides an overview of the work carried out in improving Language Model (LM) development used during the decoding of an Automatic Speech Recognition (ASR) system. The goal of this work is to develop a robust language model that can be adapted ...

Idiap2020

Simulation of Instability in Time-Sensitive Networks with Regulators and Imperfect Clocks

Guillermo Aguirre Rodrigo

Regulators are used in time-sensitive networks in order to reshape traffic reducing the burstiness generated by the aggregation systems within the network. Regulators, in terms of the IEEE TSN group are defined as Asynchronous Traffic Shaping or what in th ...

2020

Multilingual Deep Neural Network based Acoustic Modeling For Rapid Language Adaptation

Hervé Bourlard, Petr Motlicek, David Imseng

This paper presents a study on multilingual deep neural network (DNN) based acoustic modeling and its application to new languages. We investigate the effect of phone merging on multilingual DNN in context of rapid language adaptation. Moreover, the combin ...

2014

Supervised and unsupervised Web-based language model domain adaptation

Petr Motlicek, John David Scott Dines

Domain language model adaptation consists in re-estimating probabilities of a baseline LM in order to better match the specifics of a given broad topic of interest. To do so, a common strategy is to retrieve adaptation texts from the Web based on a given d ...

2012

Supervised and unsupervised Web-based language model domain adaptation

Petr Motlicek, John David Scott Dines

Idiap2012

Conversion of Recurrent Neural Network Language Models to Weighted Finite State Transducers for Automatic Speech Recognition

Petr Motlicek

Recurrent neural network language models (RNNLMs) have recently shown to outperform the venerable n-gram language models (LMs). However, in automatic speech recognition (ASR), RNNLMs were not yet used to directly decode a speech signal. Instead, RNNLMs are ...

2012

Conversion of Recurrent Neural Network Language Models to Weighted Finite State Transducers for Automatic Speech Recognition

Petr Motlicek

Idiap2012

Impact du degre de supervision sur l'adaptation a un domaine d'un modele de langage a partir du Web

Petr Motlicek, John David Scott Dines

Domain adaptation of a language model aims at re-estimating word sequence probabilities in order to better match the peculiarities of a given broad topic of interest. To achieve this task, a common strategy consists in retrieving adaptation texts from the ...

ATALA/AFCP2012

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