Brigitte Bigi


2022

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CLeLfPC: a Large Open Multi-Speaker Corpus of French Cued Speech
Brigitte Bigi | Maryvonne Zimmermann | Carine André
Proceedings of the Thirteenth Language Resources and Evaluation Conference

Cued Speech is a communication system developed for deaf people to complement speechreading at the phonetic level with hands. This visual communication mode uses handshapes in different placements near the face in combination with the mouth movements of speech to make the phonemes of spoken language look different from each other. This paper describes CLeLfPC - Corpus de Lecture en Langue française Parlée Complétée, a corpus of French Cued Speech. It consists in about 4 hours of audio and HD video recordings of 23 participants. The recordings are 160 different isolated ‘CV’ syllables repeated 5 times, 320 words or phrases repeated 2-3 times and about 350 sentences repeated 2-3 times. The corpus is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. It can be used for any further research or teaching purpose. The corpus includes orthographic transliteration and other phonetic annotations on 5 of the recorded topics, i.e. syllables, words, isolated sentences and a text. The early results are encouraging: it seems that 1/ the hand position has a high influence on the key audio duration; and 2/ the hand shape has not.

2020

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“Cheese!”: a Corpus of Face-to-face French Interactions. A Case Study for Analyzing Smiling and Conversational Humor
Béatrice Priego-Valverde | Brigitte Bigi | Mary Amoyal
Proceedings of the Twelfth Language Resources and Evaluation Conference

Cheese! is a conversational corpus. It consists of 11 French face-to-face conversations lasting around 15 minutes each. Cheese! is a duplication of an American corpus (ref) in order to conduct a cross-cultural comparison of participants’ smiling behavior in humorous and non-humorous sequences in American English and French conversations. In this article, the methodology used to collect and enrich the corpus is presented: experimental protocol, technical choices, transcription, semi-automatic annotations, manual annotations of smiling and humor. An exploratory study investigating the links between smile and humor is then proposed. Based on the analysis of two interactions, two questions are asked: (1) Does smile frame humor? (2) Does smile has an impact on its success or failure? If the experimental design of Cheese! has been elaborated to study specifically smiles and humor in conversations, the high quality of the dataset obtained, and the methodology used are also replicable and can be applied to analyze many other conversational activities and other multimodal modalities.

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Multimodal Corpus of Bidirectional Conversation of Human-human and Human-robot Interaction during fMRI Scanning
Birgit Rauchbauer | Youssef Hmamouche | Brigitte Bigi | Laurent Prévot | Magalie Ochs | Thierry Chaminade
Proceedings of the Twelfth Language Resources and Evaluation Conference

In this paper we present investigation of real-life, bi-directional conversations. We introduce the multimodal corpus derived from these natural conversations alternating between human-human and human-robot interactions. The human-robot interactions were used as a control condition for the social nature of the human-human conversations. The experimental set up consisted of conversations between the participant in a functional magnetic resonance imaging (fMRI) scanner and a human confederate or conversational robot outside the scanner room, connected via bidirectional audio and unidirectional videoconferencing (from the outside to inside the scanner). A cover story provided a framework for natural, real-life conversations about images of an advertisement campaign. During the conversations we collected a multimodal corpus for a comprehensive characterization of bi-directional conversations. In this paper we introduce this multimodal corpus which includes neural data from functional magnetic resonance imaging (fMRI), physiological data (blood flow pulse and respiration), transcribed conversational data, as well as face and eye-tracking recordings. Thus, we present a unique corpus to study human conversations including neural, physiological and behavioral data.

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Developing Resources for Automated Speech Processing of Quebec French
Mélanie Lancien | Marie-Hélène Côté | Brigitte Bigi
Proceedings of the Twelfth Language Resources and Evaluation Conference

The analysis of the structure of speech nearly always rests on the alignment of the speech recording with a phonetic transcription. Nowadays several tools can perform this speech segmentation automatically. However, none of them allows the automatic segmentation of Quebec French (QF hereafter), the acoustics and phonotactics of QF differing widely from that of France French (FF hereafter). To adequately segment QF, features like diphthongization of long vowels and affrication of coronal stops have to be taken into account. Thus acoustic models for automatic segmentation must be trained on speech samples exhibiting those phenomena. Dictionaries and lexicons must also be adapted and integrate differences in lexical units and in the phonology of QF. This paper presents the development of linguistic resources to be included into SPPAS software tool in order to get Text normalization, Phonetization, Alignment and Syllabification. We adapted the existing French lexicon and developed a QF-specific pronunciation dictionary. We then created an acoustic model from the existing ones and adapted it with 5 minutes of manually time-aligned data. These new resources are all freely distributed with SPPAS version 2.7; they perform the full process of speech segmentation in Quebec French.

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La mobilisation du tractus vocal est-elle variable selon les langues en parole spontanée ? (Does vocal tract use depend on language characteristics in spontaneous speech?)
Christine Meunier | Morgane Peirolo | Brigitte Bigi
Actes de la 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 1 : Journées d'Études sur la Parole

L’objectif de ce travail est de quantifier les positions articulatoires théoriques lors de la production de la parole spontanée dans trois langues. Chaque langue dispose d’un inventaire phonologique spécifique. Mais ces spécificités ne sont pas représentées telles quelles en parole spontanée dans laquelle les phonèmes n’ont pas tous la même fréquence d’apparition. Nous avons comparé trois langues (polonais, français et anglais américain) présentant des différences notables dans leur inventaire phonologique. Des positions articulatoires ont été calculées sur la base des fréquences des phonèmes dans chacune des trois langues dans des corpus de parole spontanée. Etonnamment, les résultats tendent à montrer que les positions articulatoires majoritaires sont très similaires dans les trois langues. Il semble ainsi que l’usage de la parole spontanée, et donc la distribution des phonèmes dans les langues, gomme les disparités des systèmes phonologiques pour tendre vers une mobilisation articulatoire commune. Des investigations plus approfondies devront vérifier cette observation.

2016

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Laughter in French Spontaneous Conversational Dialogs
Brigitte Bigi | Roxane Bertrand
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

This paper presents a quantitative description of laughter in height 1-hour French spontaneous conversations. The paper includes the raw figures for laughter as well as more details concerning inter-individual variability. It firstly describes to what extent the amount of laughter and their durations varies from speaker to speaker in all dialogs. In a second suite of analyses, this paper compares our corpus with previous analyzed corpora. In a final set of experiments, it presents some facts about overlapping laughs. This paper have quantified these all effects in free-style conversations, for the first time.

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The TYPALOC Corpus: A Collection of Various Dysarthric Speech Recordings in Read and Spontaneous Styles
Christine Meunier | Cecile Fougeron | Corinne Fredouille | Brigitte Bigi | Lise Crevier-Buchman | Elisabeth Delais-Roussarie | Laurianne Georgeton | Alain Ghio | Imed Laaridh | Thierry Legou | Claire Pillot-Loiseau | Gilles Pouchoulin
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

This paper presents the TYPALOC corpus of French Dysarthric and Healthy speech and the rationale underlying its constitution. The objective is to compare phonetic variation in the speech of dysarthric vs. healthy speakers in different speech conditions (read and unprepared speech). More precisely, we aim to compare the extent, types and location of phonetic variation within these different populations and speech conditions. The TYPALOC corpus is constituted of a selection of 28 dysarthric patients (three different pathologies) and of 12 healthy control speakers recorded while reading the same text and in a more natural continuous speech condition. Each audio signal has been segmented into Inter-Pausal Units. Then, the corpus has been manually transcribed and automatically aligned. The alignment has been corrected by an expert phonetician. Moreover, the corpus benefits from an automatic syllabification and an Automatic Detection of Acoustic Phone-Based Anomalies. Finally, in order to interpret phonetic variations due to pathologies, a perceptual evaluation of each patient has been conducted. Quantitative data are provided at the end of the paper.

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Répartition des phonèmes réduits en parole conversationnelle. Approche quantitative par extraction automatique (The distribution of reduced phoneme in conversational speech)
Meunier Christine | Brigitte Bigi
Actes de la conférence conjointe JEP-TALN-RECITAL 2016. volume 1 : JEP

Cette étude vise à mieux comprendre la répartition des réductions phonétiques présentes dans la production de parole. Nous avons sélectionné l! ensemble des phonèmes les plus courts (30ms) à partir de l! alignement d! un corpus de parole conversationnelle. Cette version contenant uniquement les phonèmes courts (V1) est comparée à la version contenant l! alignement de tous les phonèmes du corpus (V0). Les deux versions sont mises en relation avec l! annotation des mots et de leur catégorie syntaxique. Les résultats montrent que les liquides, les glissantes et les voyelles fermées sont plus représentées dans V1 que dans V0. Par ailleurs, la nature et la catégorie syntaxique des mots modulent la distribution des phonèmes en V1. Ainsi, la nature instable du /l/, ainsi que sa présence dans de très nombreux pronoms et déterminants, en fait le phonème le plus marqué par la réduction. Enfin, la fréquence des mots semble montrer des effets contradictoires.

2015

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A SIP of CoFee : A Sample of Interesting Productions of Conversational Feedback
Laurent Prévot | Jan Gorisch | Roxane Bertrand | Emilien Gorène | Brigitte Bigi
Proceedings of the 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue

2014

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Proceedings of TALN 2014 (Volume 1: Long Papers)
Philippe Blache | Frédéric Béchet | Brigitte Bigi
Proceedings of TALN 2014 (Volume 1: Long Papers)

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Proceedings of TALN 2014 (Volume 2: Short Papers)
Philippe Blache | Frédéric Béchet | Brigitte Bigi
Proceedings of TALN 2014 (Volume 2: Short Papers)

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Extracting multi-annotated speech data (Extraction de données orales multi-annotées) [in French]
Brigitte Bigi | Tatsuya Watanabe
Proceedings of TALN 2014 (Volume 2: Short Papers)

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Proceedings of TALN 2014 (Volume 3: System Demonstrations)
Grégoire de Montcheuil | Brigitte Bigi
Proceedings of TALN 2014 (Volume 3: System Demonstrations)

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Proceedings of TALN 2014 (Volume 4: RECITAL - Student Research Workshop)
Núria Gala | Klim Peshkov | Brigitte Bigi
Proceedings of TALN 2014 (Volume 4: RECITAL - Student Research Workshop)

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Representing Multimodal Linguistic Annotated data
Brigitte Bigi | Tatsuya Watanabe | Laurent Prévot
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

The question of interoperability for linguistic annotated resources covers different aspects. First, it requires a representation framework making it possible to compare, and eventually merge, different annotation schema. In this paper, a general description level representing the multimodal linguistic annotations is proposed. It focuses on time representation and on the data content representation: This paper reconsiders and enhances the current and generalized representation of annotations. An XML schema of such annotations is proposed. A Python API is also proposed. This framework is implemented in a multi-platform software and distributed under the terms of the GNU Public License.

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Automatic detection of other-repetition occurrences: application to French conversational Speech
Brigitte Bigi | Roxane Bertrand | Mathilde Guardiola
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

This paper investigates the discursive phenomenon called other-repetitions (OR), particularly in the context of spontaneous French dialogues. It focuses on their automatic detection and characterization. A method is proposed to retrieve automatically OR: this detection is based on rules that are applied on the lexical material only. This automatic detection process has been used to label other-repetitions on 8 dialogues of CID - Corpus of Interactional Data. Evaluations performed on one speaker are good with a F1-measure of 0.85. Retrieved OR occurrences are then statistically described: number of words, distance, etc.

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Aix Map Task corpus: The French multimodal corpus of task-oriented dialogue
Jan Gorisch | Corine Astésano | Ellen Gurman Bard | Brigitte Bigi | Laurent Prévot
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

This paper introduces the Aix Map Task corpus, a corpus of audio and video recordings of task-oriented dialogues. It was modelled after the original HCRC Map Task corpus. Lexical material was designed for the analysis of speech and prosody, as described in Astésano et al. (2007). The design of the lexical material, the protocol and some basic quantitative features of the existing corpus are presented. The corpus was collected under two communicative conditions, one audio-only condition and one face-to-face condition. The recordings took place in a studio and a sound attenuated booth respectively, with head-set microphones (and in the face-to-face condition with two video cameras). The recordings have been segmented into Inter-Pausal-Units and transcribed using transcription conventions containing actual productions and canonical forms of what was said. It is made publicly available online.

2013

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A quantitative view of feedback lexical markers in conversational French
Laurent Prévot | Brigitte Bigi | Roxane Bertrand
Proceedings of the SIGDIAL 2013 Conference

2012

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SPPAS : un outil << user-friendly >> pour l’alignement texte/son (SPPAS : a tool to perform text/speech alignement) [in French]
Brigitte Bigi
JEP-TALN-RECITAL 2012, Workshop DEGELS 2012: Défi GEste Langue des Signes (DEGELS 2012: Gestures and Sign Language Challenge)

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SPPAS: a tool for the phonetic segmentation of speech
Brigitte Bigi
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

SPPAS is a tool to produce automatic annotations which include utterance, word, syllabic and phonemic segmentations from a recorded speech sound and its transcription. SPPAS is distributed under the terms of the GNU Public License. It was successfully applied during the Evalita 2011 campaign, on Italian map-task dialogues. It can also deal with French, English and Chinese and there is an easy way to add other languages. The paper describes the development of resources and free tools, consisting of acoustic models, phonetic dictionaries, and libraries and programs to deal with these data. All of them are publicly available.

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Orthographic Transcription: which enrichment is required for phonetization?
Brigitte Bigi | Pauline Péri | Roxane Bertrand
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

This paper addresses the problem of the enrichment of transcriptions in the perspective of an automatic phonetization. Phonetization is the process of representing sounds with phonetic signs. There are two general ways to construct a phonetization process: rule based systems (with rules based on inference approaches or proposed by expert linguists) and dictionary based solutions which consist in storing a maximum of phonological knowledge in a lexicon. In both cases, phonetization is based on a manual transcription. Such a transcription is established on the basis of conventions that can differ depending on their working out context. This present study focuses on three different enrichments of such a transcription. Evaluations compare phonetizations obtained from automatic systems to a reference phonetized manually. The test corpus is made of three types of speech: conversational speech, read speech and political debate. A specific algorithm for the rule-based system is proposed to deal with enrichments. The final system obtained a phonetization of about 95.2% correct (from 3.7% to 5.6% error rates depending on the corpus).

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Influence de la transcription sur la phonétisation automatique de corpus oraux (what is the impact of the transcription on the phonetization) [in French]
Brigitte Bigi | Pauline Péri | Roxane Bertrand
Proceedings of the Joint Conference JEP-TALN-RECITAL 2012, volume 1: JEP

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SPPAS : segmentation, phonétisation, alignement, syllabation (SPPAS : a tool to perform text/speech alignement) [in French]
Brigitte Bigi
Proceedings of the Joint Conference JEP-TALN-RECITAL 2012, volume 5: Software Demonstrations

2011

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Catégoriser les réponses aux interruptions dans les débats politiques (Categorizing responses to disruptions in political debates)
Brigitte Bigi | Cristel Portes | Agnès Steuckardt | Marion Tellier
Actes de la 18e conférence sur le Traitement Automatique des Langues Naturelles. Articles courts

Cet article traite de l’analyse de débats politiques selon une orientation multimodale. Nous étudions plus particulièrement les réponses aux interruptions lors d’un débat à l’Assemblée nationale. Nous proposons de procéder à l’analyse via des annotations systématiques de différentes modalités. L’analyse argumentative nous a amenée à proposer une typologie de ces réponses. Celle-ci a été mise à l’épreuve d’une classification automatique. La difficulté dans la construction d’un tel système réside dans la nature même des données : multimodales, parfois manquantes et incertaines.

2010

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Automatic Detection of Syllable Boundaries in Spontaneous Speech
Brigitte Bigi | Christine Meunier | Irina Nesterenko | Roxane Bertrand
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

This paper presents the outline and performance of an automatic syllable boundary detection system. The syllabification of phonemes is performed with a rule-based system, implemented in a Java program. Phonemes are categorized into 6 classes. A set of specific rules are developed and categorized as general rules which can be applied in all cases, and exception rules which are applied in some specific situations. These rules deal with a French spontaneous speech corpus. Moreover, the proposed phonemes, classes and rules are listed in an external configuration file of the tool (under GPL licence) that make the tool very easy to adapt to a specific corpus by adding or modifying rules, phoneme encoding or phoneme classes, by the use of a new configuration file. Finally, performances are evaluated and compared to 3 other French syllabification systems and show significant improvements. Automatic system output and expert's syllabification are in agreement for most of syllable boundaries in our corpus.

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Multimodal Annotation of Conversational Data
Philippe Blache | Roxane Bertrand | Emmanuel Bruno | Brigitte Bigi | Robert Espesser | Gaelle Ferré | Mathilde Guardiola | Daniel Hirst | Ning Tan | Edlira Cela | Jean-Claude Martin | Stéphane Rauzy | Mary-Annick Morel | Elisabeth Murisasco | Irina Nesterenko
Proceedings of the Fourth Linguistic Annotation Workshop

2009

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Mining a Comparable Text Corpus for a Vietnamese-French Statistical Machine Translation System
Thi-Ngoc-Diep Do | Viet-Bac Le | Brigitte Bigi | Laurent Besacier | Eric Castelli
Proceedings of the Fourth Workshop on Statistical Machine Translation

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Exploitation d’un corpus bilingue pour la création d’un système de traduction probabiliste Vietnamien - Français
Thi-Ngoc-Diep Do | Viet-Bac Le | Brigitte Bigi | Laurent Besacier | Eric Castelli
Actes de la 16ème conférence sur le Traitement Automatique des Langues Naturelles. Articles longs

Cet article présente nos premiers travaux en vue de la construction d’un système de traduction probabiliste pour le couple de langue vietnamien-français. La langue vietnamienne étant considérée comme une langue peu dotée, une des difficultés réside dans la constitution des corpus parallèles, indispensable à l’apprentissage des modèles. Nous nous concentrons sur la constitution d’un grand corpus parallèle vietnamien-français. La méthode d’identification automatique des paires de documents parallèles fondée sur la date de publication, les mots spéciaux et les scores d’alignements des phrases est appliquée. Cet article présente également la construction d’un premier système de traduction automatique probabiliste vietnamienfrançais et français-vietnamien à partir de ce corpus et discute l’opportunité d’utiliser des unités lexicales ou sous-lexicales pour le vietnamien (syllabes, mots, ou leurs combinaisons). Les performances du système sont encourageantes et se comparent avantageusement à celles du système de Google.

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Segmentation multiple d’un flux de données textuelles pour la modélisation statistique du langage
Sopheap Seng | Laurent Besacier | Brigitte Bigi | Eric Castelli
Actes de la 16ème conférence sur le Traitement Automatique des Langues Naturelles. Articles courts

Dans cet article, nous traitons du problème de la modélisation statistique du langage pour les langues peu dotées et sans segmentation entre les mots. Tandis que le manque de données textuelles a un impact sur la performance des modèles, les erreurs introduites par la segmentation automatique peuvent rendre ces données encore moins exploitables. Pour exploiter au mieux les données textuelles, nous proposons une méthode qui effectue des segmentations multiples sur le corpus d’apprentissage au lieu d’une segmentation unique. Cette méthode basée sur les automates d’état finis permet de retrouver les n-grammes non trouvés par la segmentation unique et de générer des nouveaux n-grammes pour l’apprentissage de modèle du langage. L’application de cette approche pour l’apprentissage des modèles de langage pour les systèmes de reconnaissance automatique de la parole en langue khmère et vietnamienne s’est montrée plus performante que la méthode par segmentation unique, à base de règles.

2008

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First Broadcast News Transcription System for Khmer Language
Sopheap Seng | Sethserey Sam | Laurent Besacier | Brigitte Bigi | Eric Castelli
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

In this paper we present an overview on the development of a large vocabulary continuous speech recognition (LVCSR) system for Khmer, the official language of Cambodia, spoken by more than 15 million people. As an under-resourced language, develop a LVCSR system for Khmer is a challenging task. We describe our methodologies for quick language data collection and processing for language modeling and acoustic modeling. For language modeling, we investigate the use of word and sub-word as basic modeling unit in order to see the potential of sub-word units in the case of unsegmented language like Khmer. Grapheme-based acoustic modeling is used to quickly build our Khmer language acoustic model. Furthermore, the approaches and tools used for the development of our system are documented and made publicly available on the web. We hope this will contribute to accelerate the development of LVCSR system for a new language, especially for under-resource languages of developing countries where resources and expertise are limited.

2004

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Modèle de langage sémantique pour la reconnaissance automatique de parole dans un contexte de traduction
Quang Vu-minh | Laurent Besacier | Hervé Blanchon | Brigitte Bigi
Actes de la 11ème conférence sur le Traitement Automatique des Langues Naturelles. Posters

Le travail présenté dans cet article a été réalisé dans le cadre d’un projet global de traduction automatique de la parole. L’approche de traduction est fondée sur un langage pivot ou Interchange Format (IF), qui représente le sens de la phrase indépendamment de la langue. Nous proposons une méthode qui intègre des informations sémantiques dans le modèle statistique de langage du système de Reconnaissance Automatique de Parole. Le principe consiste a utiliser certaines classes définies dans l’IF comme des classes sémantiques dans le modèle de langage. Ceci permet au système de reconnaissance de la parole d’analyser partiellement en IF les tours de parole. Les expérimentations realisées montrent qu’avec cette approche, le système de reconnaissance peut analyser directement en IF une partie des données de dialogues de notre application, sans faire appel au système de traduction (35% des mots ; 58% des tours de parole), tout en maintenant le même niveau de performance du système global.

2002

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Identification thématique hiérarchique : Application aux forums de discussions
Brigitte Bigi | Kamel Smaïli
Actes de la 9ème conférence sur le Traitement Automatique des Langues Naturelles. Articles longs

Les modèles statistiques du langage ont pour but de donner une représentation statistique de la langue mais souffrent de nombreuses imperfections. Des travaux récents ont montré que ces modèles peuvent être améliorés s’ils peuvent bénéficier de la connaissance du thème traité, afin de s’y adapter. Le thème du document est alors obtenu par un mécanisme d’identification thématique, mais les thèmes ainsi traités sont souvent de granularité différente, c’est pourquoi il nous semble opportun qu’ils soient organisés dans une hiérarchie. Cette structuration des thèmes implique la mise en place de techniques spécifiques d’identification thématique. Cet article propose un modèle statistique à base d’unigrammes pour identifier automatiquement le thème d’un document parmi une arborescence prédéfinie de thèmes possibles. Nous présentons également un critère qui permet au modèle de donner un degré de fiabilité à la décision prise. L’ensemble des expérimentations a été réalisé sur des données extraites du groupe ’fr’ des forums de discussion.