Solen Quiniou - Academia.edu (original) (raw)
Papers by Solen Quiniou
![Research paper thumbnail of Segmentation automatique d’un texte en rhèses (Automatic segmentation of a text into rhesis)[In French]](https://attachments.academia-assets.com/97563730/thumbnails/1.jpg)
](La segmentation d’un texte en rhèses, unités-membres signifiantes de la phrase, permet de fournir... more La segmentation d’un texte en rhèses, unités-membres signifiantes de la phrase, permet de fournir des adaptations de celui-ci pour faciliter la lecture aux personnes dyslexiques. Dans cet article, nous proposons une méthode d’identification automatique des rhèses basée sur un apprentissage supervisé à partir d’un corpus que nous avons annoté. Nous comparons celle-ci à l’identification manuelle ainsi qu’à l’utilisation d’outils et de concepts proches, tels que la segmentation d’un texte en chunks.
ArXiv, 2019
The emergence of the digital book is a major step forward in providing access to reading, and the... more The emergence of the digital book is a major step forward in providing access to reading, and therefore often to the common culture and the labour market. By allowing the enrichment of texts with cognitive crutches, EPub 3 compatible accessibility formats such as FROG have proven their effectiveness in alleviating but also reducing dyslexic disorders. In this paper, we show how Artificial Intelligence and particularly Transfer Learning with Google BERT can automate the division into units of meaning, and thus facilitate the creation of enriched digital books at a moderate cost.
La segmentation d'un texte en rheses, unites-membres signifiantes de la phrase, permet de fou... more La segmentation d'un texte en rheses, unites-membres signifiantes de la phrase, permet de fournir des adaptations de celui-ci pour faciliter la lecture aux personnes dyslexiques. Dans cet article, nous proposons une methode d'identification automatique des rheses basee sur un apprentissage supervise a partir d'un corpus que nous avons annote. Nous comparons celle-ci a l'identification manuelle ainsi qu'a l'utilisation d'outils et de concepts proches, tels que la segmentation d'un texte en chunks.
Children's books are generally designed for children of a certain age group. For underage chi... more Children's books are generally designed for children of a certain age group. For underage children or children with reading disorders, like dyslexia, there may be passages of the books that are difficult to understand. This can be due to words not known in the vocabulary of underage children, to words made of complex subparts (to pronounce, for example), or to the presence of anaphoras that have to be resolved by the children during the reading. In this paper, we present a study on diagnosing the difficulties appearing in French children's books. We are more particularly interested on the difficulties coming from pronouns that can disrupt the story comprehension for children with dyslexia and we focus on the subject pronouns " il " and " elle " (corresponding to the pronoun " it "). We automatically identify the pleonastic pronouns (e.g., in " it's raining ") and the pronominal anaphoras, as well as the referents of the pronominal ...
Ninth International Conference on Document Analysis and Recognition (ICDAR 2007), 2007
In this paper we investigate the integration of a confusion network into an on-line handwritten s... more In this paper we investigate the integration of a confusion network into an on-line handwritten sentence recognition system. The word posterior probabilities from the confusion network are used as confidence scored to detect potential errors in the output sentence from the Maximum A Posteriori decoding on a word graph. Dedicated classifiers (here, SVMs) are then trained to correct these errors and combine the word posterior probabilities with other sources of knowledge. A rejection phase is also introduced in the detection process. Experiments on handwritten sentences show a 28.5 % relative reduction of the word error rate.
International Journal of Pattern Recognition and Artificial Intelligence, 2009
This paper presents a word extraction approach based on the use of a confidence index to limit th... more This paper presents a word extraction approach based on the use of a confidence index to limit the total number of segmentation hypotheses in order to further extend our online sentence recognition system to perform "on-the-fly" recognition. Our initial word extraction task is based on the characterization of the gap between each couple of consecutive strokes from the online signal of the handwritten sentence. A confidence index is associated to the gap classification result in order to evaluate its reliability. A reconsideration process is then performed to create additional segmentation hypotheses to ensure the presence of the correct segmentation among the hypotheses. In this process, we control the total number of segmentation hypotheses to limit the complexity of the recognition process and thus the execution time. This approach is evaluated on a test set of 425 English sentences written by 17 writers, using different metrics to analyze the impact of the word extracti...
International Journal on Document Analysis and Recognition (IJDAR), 2011
In this paper, we present a framework to handle recognition errors from a N-best list of output p... more In this paper, we present a framework to handle recognition errors from a N-best list of output phrases given by a handwriting recognition system, with the aim to use the resulting phrases as inputs to a higher-level application. The framework can be decomposed into four main steps: phrase alignment, detection, characterization, and correction of word error hypotheses. First, the N-best phrases are aligned to the top-list phrase, and word posterior probabilities are computed and used as confidence indices to detect word error hypotheses on this top-list phrase (in comparison with a learned threshold). Then, the errors are characterized into predefined types, using the word posterior probabilities of the top-list phrase and other features to feed a trained SVM. Finally, the final output phrase is retrieved, thanks to a correction step that used the characterized error hypotheses and a designed word-to-class backoff language model. First experiments were conducted on the ImadocSen-OnDB handwritten sentence database and on the IAM-OnDB handwritten text database, using two recognizers. We present first results on an implementation of the proposed framework for handling recognition errors on transcripts of handwritten phrases provided by recognition systems.
2009 10th International Conference on Document Analysis and Recognition, 2009
In this paper we investigate the use of linguistic information given by language models to deal w... more In this paper we investigate the use of linguistic information given by language models to deal with word recognition errors on handwritten sentences. We focus especially on errors due to out-of-vocabulary (OOV) words. First, word posterior probabilities are computed and used to detect error hypotheses on output sentences. An SVM classifier allows these errors to be categorized according to defined types. Then, a post-processing step is performed using a language model based on Part-of-Speech (POS) tags which is combined to the n-gram model previously used. Thus, error hypotheses can be further recognized and POS tags can be assigned to the OOV words. Experiments on on-line handwritten sentences show that the proposed approach allows a significant reduction of the word error rate.
2010 20th International Conference on Pattern Recognition, 2010
In this paper, we present a new method to design customizable self-evolving fuzzy rule-based clas... more In this paper, we present a new method to design customizable self-evolving fuzzy rule-based classifiers. The presented approach combines an incremental clustering algorithm with a fuzzy adaptation method in order to learn and maintain the model. We use this method to build an evolving handwritten gesture recognition system. The self-adaptive nature of this system allows it to start its learning process with few learning data, to continuously adapt and evolve according to any new data, and to remain robust when introducing a new unseen class at any moment in the lifelong learning process.
2010 12th International Conference on Frontiers in Handwriting Recognition, 2010
In this paper, we present a new method to design customizable self-evolving fuzzy rule-based clas... more In this paper, we present a new method to design customizable self-evolving fuzzy rule-based classifiers. The presented approach combines an incremental clustering algorithm with a fuzzy adaptation method in order to learn and maintain the model. We use this method to build an evolving handwritten gesture recognition system, that can be integrated into an application to provide personalization capabilities. Experiments on an on-line gesture database were performed by considering various user personalization scenarios. The experiments show that the proposed evolving gesture recognition system continuously adapts and evolve according to new data of learned classes, and remains robust when introducing new unseen classes, at any moment during the lifelong learning process.
Dans cet article, nous présentons un système complet de reconnaissance de phrases manuscrites en-... more Dans cet article, nous présentons un système complet de reconnaissance de phrases manuscrites en-ligne. Nous nous intéressons plus particulièrement à la détection d'erreurs potentielles sur les phrases issues d'une reconnaissance avec une approche au Maximum A Posteriori. Les probabilités a posteriori des mots, obtenues à partir d'une représentation sous la forme d'un réseau de confusion, sont ainsi utilisées comme indices de confiance. Des classifieurs dédiés (ici, des SVM) sont ensuite appris afin de corriger ces erreurs, en combinant ces probabilités a posteriori à d'autres sources de connaissance. Un mécanisme de rejet est également introduit afin de distinguer les hypothèses d'erreur qui ne pourront être corrigées par l'approche proposée. Des expérimentations ont été menées sur une base de 425 phrases manuscrites écrites par 17 scripteurs. Elles ont mis en évidence une réduction relative du taux d'erreur sur les mots de 14,6 %.
We present a framework based on the standard InkML format to represent digital ink in a collabora... more We present a framework based on the standard InkML format to represent digital ink in a collaborative environment using pen-based interaction functionalities. This framework includes the capture, the rendering and the interpretation of the digital ink. In the proposed framework, we focus more particularly on the representation of the contextual environment of the ink and used for its interpretation (as drawing, for example) as well as on the representation of semantic information attached to the ink after its interpretation.
La segmentation d’un texte en rhèses, unités-membres signifiantes de la phrase, permet de fournir... more La segmentation d’un texte en rhèses, unités-membres signifiantes de la phrase, permet de fournir des adaptations de celui-ci pour faciliter la lecture aux personnes dyslexiques. Dans cet article, nous proposons une méthode d’identification automatique des rhèses basée sur un apprentissage supervisé à partir d’un corpus que nous avons annoté. Nous comparons celle-ci à l’identification manuelle ainsi qu’à l’utilisation d’outils et de concepts proches, tels que la segmentation d’un texte en chunks.
ArXiv, 2019
The emergence of the digital book is a major step forward in providing access to reading, and the... more The emergence of the digital book is a major step forward in providing access to reading, and therefore often to the common culture and the labour market. By allowing the enrichment of texts with cognitive crutches, EPub 3 compatible accessibility formats such as FROG have proven their effectiveness in alleviating but also reducing dyslexic disorders. In this paper, we show how Artificial Intelligence and particularly Transfer Learning with Google BERT can automate the division into units of meaning, and thus facilitate the creation of enriched digital books at a moderate cost.
La segmentation d'un texte en rheses, unites-membres signifiantes de la phrase, permet de fou... more La segmentation d'un texte en rheses, unites-membres signifiantes de la phrase, permet de fournir des adaptations de celui-ci pour faciliter la lecture aux personnes dyslexiques. Dans cet article, nous proposons une methode d'identification automatique des rheses basee sur un apprentissage supervise a partir d'un corpus que nous avons annote. Nous comparons celle-ci a l'identification manuelle ainsi qu'a l'utilisation d'outils et de concepts proches, tels que la segmentation d'un texte en chunks.
Children's books are generally designed for children of a certain age group. For underage chi... more Children's books are generally designed for children of a certain age group. For underage children or children with reading disorders, like dyslexia, there may be passages of the books that are difficult to understand. This can be due to words not known in the vocabulary of underage children, to words made of complex subparts (to pronounce, for example), or to the presence of anaphoras that have to be resolved by the children during the reading. In this paper, we present a study on diagnosing the difficulties appearing in French children's books. We are more particularly interested on the difficulties coming from pronouns that can disrupt the story comprehension for children with dyslexia and we focus on the subject pronouns " il " and " elle " (corresponding to the pronoun " it "). We automatically identify the pleonastic pronouns (e.g., in " it's raining ") and the pronominal anaphoras, as well as the referents of the pronominal ...
Ninth International Conference on Document Analysis and Recognition (ICDAR 2007), 2007
In this paper we investigate the integration of a confusion network into an on-line handwritten s... more In this paper we investigate the integration of a confusion network into an on-line handwritten sentence recognition system. The word posterior probabilities from the confusion network are used as confidence scored to detect potential errors in the output sentence from the Maximum A Posteriori decoding on a word graph. Dedicated classifiers (here, SVMs) are then trained to correct these errors and combine the word posterior probabilities with other sources of knowledge. A rejection phase is also introduced in the detection process. Experiments on handwritten sentences show a 28.5 % relative reduction of the word error rate.
International Journal of Pattern Recognition and Artificial Intelligence, 2009
This paper presents a word extraction approach based on the use of a confidence index to limit th... more This paper presents a word extraction approach based on the use of a confidence index to limit the total number of segmentation hypotheses in order to further extend our online sentence recognition system to perform "on-the-fly" recognition. Our initial word extraction task is based on the characterization of the gap between each couple of consecutive strokes from the online signal of the handwritten sentence. A confidence index is associated to the gap classification result in order to evaluate its reliability. A reconsideration process is then performed to create additional segmentation hypotheses to ensure the presence of the correct segmentation among the hypotheses. In this process, we control the total number of segmentation hypotheses to limit the complexity of the recognition process and thus the execution time. This approach is evaluated on a test set of 425 English sentences written by 17 writers, using different metrics to analyze the impact of the word extracti...
International Journal on Document Analysis and Recognition (IJDAR), 2011
In this paper, we present a framework to handle recognition errors from a N-best list of output p... more In this paper, we present a framework to handle recognition errors from a N-best list of output phrases given by a handwriting recognition system, with the aim to use the resulting phrases as inputs to a higher-level application. The framework can be decomposed into four main steps: phrase alignment, detection, characterization, and correction of word error hypotheses. First, the N-best phrases are aligned to the top-list phrase, and word posterior probabilities are computed and used as confidence indices to detect word error hypotheses on this top-list phrase (in comparison with a learned threshold). Then, the errors are characterized into predefined types, using the word posterior probabilities of the top-list phrase and other features to feed a trained SVM. Finally, the final output phrase is retrieved, thanks to a correction step that used the characterized error hypotheses and a designed word-to-class backoff language model. First experiments were conducted on the ImadocSen-OnDB handwritten sentence database and on the IAM-OnDB handwritten text database, using two recognizers. We present first results on an implementation of the proposed framework for handling recognition errors on transcripts of handwritten phrases provided by recognition systems.
2009 10th International Conference on Document Analysis and Recognition, 2009
In this paper we investigate the use of linguistic information given by language models to deal w... more In this paper we investigate the use of linguistic information given by language models to deal with word recognition errors on handwritten sentences. We focus especially on errors due to out-of-vocabulary (OOV) words. First, word posterior probabilities are computed and used to detect error hypotheses on output sentences. An SVM classifier allows these errors to be categorized according to defined types. Then, a post-processing step is performed using a language model based on Part-of-Speech (POS) tags which is combined to the n-gram model previously used. Thus, error hypotheses can be further recognized and POS tags can be assigned to the OOV words. Experiments on on-line handwritten sentences show that the proposed approach allows a significant reduction of the word error rate.
2010 20th International Conference on Pattern Recognition, 2010
In this paper, we present a new method to design customizable self-evolving fuzzy rule-based clas... more In this paper, we present a new method to design customizable self-evolving fuzzy rule-based classifiers. The presented approach combines an incremental clustering algorithm with a fuzzy adaptation method in order to learn and maintain the model. We use this method to build an evolving handwritten gesture recognition system. The self-adaptive nature of this system allows it to start its learning process with few learning data, to continuously adapt and evolve according to any new data, and to remain robust when introducing a new unseen class at any moment in the lifelong learning process.
2010 12th International Conference on Frontiers in Handwriting Recognition, 2010
In this paper, we present a new method to design customizable self-evolving fuzzy rule-based clas... more In this paper, we present a new method to design customizable self-evolving fuzzy rule-based classifiers. The presented approach combines an incremental clustering algorithm with a fuzzy adaptation method in order to learn and maintain the model. We use this method to build an evolving handwritten gesture recognition system, that can be integrated into an application to provide personalization capabilities. Experiments on an on-line gesture database were performed by considering various user personalization scenarios. The experiments show that the proposed evolving gesture recognition system continuously adapts and evolve according to new data of learned classes, and remains robust when introducing new unseen classes, at any moment during the lifelong learning process.
Dans cet article, nous présentons un système complet de reconnaissance de phrases manuscrites en-... more Dans cet article, nous présentons un système complet de reconnaissance de phrases manuscrites en-ligne. Nous nous intéressons plus particulièrement à la détection d'erreurs potentielles sur les phrases issues d'une reconnaissance avec une approche au Maximum A Posteriori. Les probabilités a posteriori des mots, obtenues à partir d'une représentation sous la forme d'un réseau de confusion, sont ainsi utilisées comme indices de confiance. Des classifieurs dédiés (ici, des SVM) sont ensuite appris afin de corriger ces erreurs, en combinant ces probabilités a posteriori à d'autres sources de connaissance. Un mécanisme de rejet est également introduit afin de distinguer les hypothèses d'erreur qui ne pourront être corrigées par l'approche proposée. Des expérimentations ont été menées sur une base de 425 phrases manuscrites écrites par 17 scripteurs. Elles ont mis en évidence une réduction relative du taux d'erreur sur les mots de 14,6 %.
We present a framework based on the standard InkML format to represent digital ink in a collabora... more We present a framework based on the standard InkML format to represent digital ink in a collaborative environment using pen-based interaction functionalities. This framework includes the capture, the rendering and the interpretation of the digital ink. In the proposed framework, we focus more particularly on the representation of the contextual environment of the ink and used for its interpretation (as drawing, for example) as well as on the representation of semantic information attached to the ink after its interpretation.