Concept

Glyphe

Publications associées (10)

How to Tell Ancient Signs Apart? Recognizing and Visualizing Maya Glyphs with CNNs

Daniel Gatica-Perez, Jean-Marc Odobez, Gülcan Can

Thanks to the digital preservation of cultural heritage materials, multimedia tools (e.g., based on automatic visual processing) considerably ease the work of scholars in the humanities and help them to perform quantitative analysis of their data. In this ...

2018

Acoustic data-driven grapheme-to-phoneme conversion in the probabilistic lexical modeling framework

Ramya Rasipuram, Marzieh Razavi

One of the primary steps in building automatic speech recognition (ASR) and text-to-speech systems is the development of a phonemic lexicon that provides a mapping between each word and its pronunciation as a sequence of phonemes. Phoneme lexicons can be d ...

2016

Grapheme-based Automatic Speech Recognition using Probabilistic Lexical Modeling

Ramya Rasipuram

Automatic speech recognition (ASR) systems incorporate expert knowledge of language or the linguistic expertise through the use of phone pronunciation lexicon (or dictionary) where each word is associated with a sequence of phones. The creation of phone pr ...

EPFL2014

Improving Grapheme-based ASR by Probabilistic Lexical Modeling Approach

Ramya Rasipuram

There is growing interest in using graphemes as subword units, especially in the context of the rapid development of hidden Markov model (HMM) based automatic speech recognition (ASR) system, as it eliminates the need to build a phoneme pronunciation lexic ...

2013

Grapheme-based Automatic Speech Recognition using KL-HMM

Hervé Bourlard, Ramya Rasipuram, Guillermo Aradilla

The state-of-the-art automatic speech recognition (ASR) systems typically use phonemes as subword units. In this work, we present a novel grapheme-based ASR system that jointly models phoneme and grapheme information using Kullback-Leibler divergence-based ...

2011

On Joint Modelling of Grapheme and Phoneme Information using KL-HMM for ASR

Hervé Bourlard, Guillermo Aradilla

In this paper, we propose a simple approach to jointly model both grapheme and phoneme information using Kullback-Leibler divergence based HMM (KL-HMM) system. More specifically, graphemes are used as subword units and phoneme posterior probabilities estim ...

Idiap2009

Improving Continuous Speech Recognition System Performance with Grapheme Modelling

Hervé Bourlard, Hynek Hermansky, John David Scott Dines

This paper investigates automatic speech recognition system using context-dependent graphemes as subword units based on the conventional HMM/GMM system as well as TANDEM system. Experimental studies conducted on two different continuous speech recognition ...

IDIAP2005

Phoneme vs Grapheme Based Automatic Speech Recognition

Hervé Bourlard, Hynek Hermansky, John David Scott Dines

In recent literature, different approaches have been proposed to use graphemes as subword units with implicit source of phoneme information for automatic speech recognition. The major advantage of using graphemes as subword units is that the definition of ...

IDIAP2004

Joint Decoding for Phoneme-Grapheme Continuous Speech Recognition

Hervé Bourlard, Samy Bengio

Standard ASR systems typically use phoneme as the subword units. Preliminary studies have shown that the performance of the ASR system could be improved by using grapheme as additional subword units. In this paper, we investigate such a system where the wo ...

2004

Joint Decoding for Phoneme-Grapheme Continuous Speech Recognition

Hervé Bourlard, Samy Bengio

IDIAP2003

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