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Dive into the research topics where Sophie Roekhaut is active.

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Featured researches published by Sophie Roekhaut.


spoken language technology workshop | 2012

Train&align: A new online tool for automatic phonetic alignment

Sandrine Brognaux; Sophie Roekhaut; Thomas Drugman; Richard Beaufort

Several automatic phonetic alignment tools have been proposed in the literature. They usually rely on pre-trained speaker-independent models to align new corpora. Their drawback is that they cover a very limited number of languages and might not perform properly for different speaking styles. This paper presents a new tool for automatic phonetic alignment available online. Its specificity is that it trains the model directly on the corpus to align, which makes it applicable to any language and speaking style. Experiments on three corpora show that it provides results comparable to other existing tools. It also allows the tuning of some training parameters. The use of tied-state triphones, for example, shows further improvement of about 1.5% for a 20 ms threshold. A manually-aligned part of the corpus can also be used as bootstrap to improve the model quality. Alignment rates were found to significantly increase, up to 20%, using only 30 seconds of bootstrapping data.


International Conference on NLP | 2012

Automatic Phone Alignment

Sandrine Brognaux; Sophie Roekhaut; Thomas Drugman; Richard Beaufort

Several automatic phonetic alignment tools have been proposed in the literature. They generally use speaker-independent acoustic models of the language to align new corpora. The problem is that the range of provided models is limited. It does not cover all languages and speaking styles (spontaneous, expressive, etc.). This study investigates the possibility of directly training the statistical model on the corpus to align. The main advantage is that it is applicable to any language and speaking style. Moreover, comparisons indicate that it provides as good or better results than using speaker-independent models of the language. It shows that about 2% are gained, with a 20 ms threshold, by using our method. Experiments were carried out on neutral and expressive corpora in French and English. The study also points out that even a small neutral corpus of a few minutes can be exploited to train a model that will provide high-quality alignment.


Journal of French Language Studies | 2017

Social media, spontaneous writing and dictation. Spelling variation

Louise-Amélie Cougnon; Lénaïs Maskens; Sophie Roekhaut; Cédrick Fairon

This study investigates the hypothesis of young people having the multi-skills required to switch between formal and informal communication. We collected samples of the written output of students across different media and communication situations. The results obtained through dictation tests show that the students’ level is relatively low, with a majority of grammatical errors. The analysis of linguistic forms common to the corpora indicates that all the participants use traditional spelling in at least one of them. Lastly, we present a qualitative analysis of spelling variation and an overview of the teenagers’ linguistic representations.


meeting of the association for computational linguistics | 2010

A Hybrid Rule/Model-Based Finite-State Framework for Normalizing SMS Messages

Richard Beaufort; Sophie Roekhaut; Louise-Amélie Cougnon; Cédrick Fairon


Proceedings Speech Prosody 2010 | 2010

Prominence perception and accent detection in French. A corpus-based account

Jean-Philippe Goldman; Antoine Auchlin; Sophie Roekhaut; Anne-Catherine Simon; Mathieu Avanzi


Proceedings Speech Prosody 2010 | 2010

A Model for Varying Speaking Style in TTS systems

Sophie Roekhaut; Jean-Philippe Goldman; Anne-Catherine Simon


conference of the international speech communication association | 2014

eLite-HTS: a NLP tool for French HMM-based speech synthesis

Sophie Roekhaut; Sandrine Brognaux; Richard Beaufort; Thierry Dutoit


XXVIIIèmes journées d'étude sur la parole (JEP 2010) | 2010

Étude statistique de la durée pausale dans différents styles de parole

Jean-Philippe Goldman; Thomas François; Sophie Roekhaut; Anne-Catherine Simon


Lecture Notes in Computer Science | 2012

Automatic Phone Alignment. A Comparison between Speaker-Independent Models and Models Trained on the Corpus to Align.

Sandrine Brognaux; Sophie Roekhaut; Thomas Drugman; Richard Beaufort


JADT2008 : actes des 9es Journées internationales d’Analyse statistique des Données Textuelles | 2008

Définition d'un système d'alignement SMS/Français standard à l'aide d'un filtre de composition

Richard Beaufort; Cédrick Fairon; Sophie Roekhaut

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Richard Beaufort

Université catholique de Louvain

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Cédrick Fairon

Université catholique de Louvain

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Sandrine Brognaux

Université catholique de Louvain

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Richard Beaufort

Université catholique de Louvain

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Louise-Amélie Cougnon

Université catholique de Louvain

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Anne-Catherine Simon

Université catholique de Louvain

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Thomas François

Université catholique de Louvain

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Laurence Martin

Université catholique de Louvain

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