Frédéric Landragin


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French Coreference for Spoken and Written Language
Rodrigo Wilkens | Bruno Oberle | Frédéric Landragin | Amalia Todirascu
Proceedings of the 12th Language Resources and Evaluation Conference

Coreference resolution aims at identifying and grouping all mentions referring to the same entity. In French, most systems run different setups, making their comparison difficult. In this paper, we present an extensive comparison of several coreference resolution systems for French. The systems have been trained on two corpora (ANCOR for spoken language and Democrat for written language) annotated with coreference chains, and augmented with syntactic and semantic information. The models are compared with different configurations (e.g. with and without singletons). In addition, we evaluate mention detection and coreference resolution apart. We present a full-stack model that outperforms other approaches. This model allows us to study the impact of mention detection errors on coreference resolution. Our analysis shows that mention detection can be improved by focusing on boundary identification while advances in the pronoun-noun relation detection can help the coreference task. Another contribution of this work is the first end-to-end neural French coreference resolution model trained on Democrat (written texts), which compares to the state-of-the-art systems for oral French.


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ANCOR-AS: Enriching the ANCOR Corpus with Syntactic Annotations
Loïc Grobol | Isabelle Tellier | Éric de la Clergerie | Marco Dinarelli | Frédéric Landragin
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

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Predicting failure of a mediated conversation in the context of asymetric role dialogues
Romain Carbou | Delphine Charlet | Géraldine Damnati | Frédéric Landragin | Jean Léon Bouraoui
Actes de la Conférence TALN. Volume 1 - Articles longs, articles courts de TALN

In a human-to-human conversation between a user and his interlocutor in an assistance center, we suppose a context where the conclusion of the dialog can characterize a notion of success or failure, explicitly annotated or deduced. The study involves different approaches expected to have an influence on predictive classification model of failures. On the one hand, we will aim at taking into account the asymmetry of the speakers’ roles in the modelling of the lexical distribution. On the other hand, we will determine whether the part of the lexicon most closely relating to the domain of customer assistance studied here, modifies the quality of the prediction. We will eventually assess the perspectives of generalization to morphologically comparable corpora.


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Apports des analyses syntaxiques pour la détection automatique de mentions dans un corpus de français oral (Experiences in using deep and shallow parsing to detect entity mentions in oral French)
Loïc Grobol | Isabelle Tellier | Éric de La Clergerie | Marco Dinarelli | Frédéric Landragin
Actes des 24ème Conférence sur le Traitement Automatique des Langues Naturelles. Volume 2 - Articles courts

Cet article présente trois expériences de détection de mentions dans un corpus de français oral : ANCOR. Ces expériences utilisent des outils préexistants d’analyse syntaxique du français et des méthodes issues de travaux sur la coréférence, les anaphores et la détection d’entités nommées. Bien que ces outils ne soient pas optimisés pour le traitement de l’oral, la qualité de la détection des mentions que nous obtenons est comparable à l’état de l’art des systèmes conçus pour l’écrit dans d’autres langues. Nous concluons en proposant des perspectives pour l’amélioration des résultats que nous obtenons et la construction d’un système end-to-end pour lequel nos expériences peuvent servir de base de travail.

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Automatic Measures to Characterise Verbal Alignment in Human-Agent Interaction
Guillaume Dubuisson Duplessis | Chloé Clavel | Frédéric Landragin
Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue

This work aims at characterising verbal alignment processes for improving virtual agent communicative capabilities. We propose computationally inexpensive measures of verbal alignment based on expression repetition in dyadic textual dialogues. Using these measures, we present a contrastive study between Human-Human and Human-Agent dialogues on a negotiation task. We exhibit quantitative differences in the strength and orientation of verbal alignment showing the ability of our approach to characterise important aspects of verbal alignment.

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Interoperable annotation of (co)references in the Democrat project
Loïc Grobol | Frédéric Landragin | Serge Heiden
Proceedings of the 13th Joint ISO-ACL Workshop on Interoperable Semantic Annotation (ISA-13)


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Apprentissage automatique d’un modèle de résolution de la coréférence à partir de données orales transcrites du français : le système CROC
Adèle Désoyer | Frédéric Landragin | Isabelle Tellier
Actes de la 22e conférence sur le Traitement Automatique des Langues Naturelles. Articles courts

Cet article présente CROC 1 (Coreference Resolution for Oral Corpus), un premier système de résolution des coréférences en français reposant sur des techniques d’apprentissage automatique. Une des spécificités du système réside dans son apprentissage sur des données exclusivement orales, à savoir ANCOR (anaphore et coréférence dans les corpus oraux), le premier corpus de français oral transcrit annoté en relations anaphoriques. En l’état actuel, le système CROC nécessite un repérage préalable des mentions. Nous détaillons les choix des traits – issus du corpus ou calculés – utilisés par l’apprentissage, et nous présentons un ensemble d’expérimentations avec ces traits. Les scores obtenus sont très proches de ceux de l’état de l’art des systèmes conçus pour l’écrit. Nous concluons alors en donnant des perspectives sur la réalisation d’un système end-to-end valable à la fois pour l’oral transcrit et l’écrit.


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ANALEC: a New Tool for the Dynamic Annotation of Textual Data
Frédéric Landragin | Thierry Poibeau | Bernard Victorri
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

We introduce ANALEC, a tool which aim is to bring together corpus annotation, visualization and query management. Our main idea is to provide a unified and dynamic way of annotating textual data. ANALEC allows researchers to dynamically build their own annotation scheme and use the possibilities of scheme revision, data querying and graphical visualization during the annotation process. Each query result can be visualized using a graphical representation that puts forward a set of annotations that can be directly corrected or completed. Text annotation is then considered as a cyclic process. We show that statistics like frequencies and correlations make it possible to verify annotated data on the fly during the annotation. In this paper we introduce the annotation functionalities of ANALEC, some of the annotated data visualization functionalities, and three statistical modules: frequency, correlation and geometrical representations. Some examples dealing with reference and coreference annotation illustrate the main contributions of ANALEC.


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Multimodal Meaning Representation for Generic Dialogue Systems Architectures
Frédéric Landragin | Alexandre Denis | Annalisa Ricci | Laurent Romary
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

An unified language for the communicative acts between agents is essential for the design of multi-agents architectures. Whatever the type of interaction (linguistic, multimodal, including particular aspects such as force feedback), whatever the type of application (command dialogue, request dialogue, database querying), the concepts are common and we need a generic meta-model. In order to tend towards task-independent systems, we need to clarify the modules parameterization procedures. In this paper, we focus on the characteristics of a meta-model designed to represent meaning in linguistic and multimodal applications. This meta-model is called MMIL for MultiModal Interface Language, and has first been specified in the framework of the IST MIAMM European project. What we want to test here is how relevant is MMIL for a completely different context (a different task, a different interaction type, a different linguistic domain). We detail the exploitation of MMIL in the framework of the IST OZONE European project, and we draw the conclusions on the role of MMIL in the parameterization of task-independent dialogue managers.