PADIC: extension and new experiments

International audiencePADIC is a multidialectal parallel Arabic corpus. It was composed initially by five Arabic dialects, three from the Maghreb and two from the Middle East, in addition to standard Arabic. In this paper, we present an augmented version of PADIC with a Moroccan dialect. We give also an evaluation, using the σ–index, of the computerization level of the Arabic dialects present in PADIC which reveals that these languages are really under-resourced. Several experiments in machine translation, in both sides between all the combinations of language pairs, are discussed too. For each language, we interpolated the corresponding Language Model (LM) with a large Arabic corpus based LM. The results show that this interpolation is in some cases without effect on the performances of translation systems and in others is rather penalizing

A Fine-grained Multilingual Analysis Based on the Appraisal Theory: Application to Arabic and English Videos

International audienceThe objective of this paper is to compare the opinions of two videos in two different languages. To do so, a fine-grained approach inspired from the appraisal theory is used to analyze the content of the videos that concern the same topic. In general, the methods devoted to sentiment analysis concern the study of the polarity of a text or an utterance. The appraisal approach goes further than the basic polarity sentiments and consider more detailed sentiments by covering additional attributes of opinions such as: Attitude, Graduation and Engagement. In order to achieve such a comparison, in AMIS (Chist-Era project), we collected a corpus of 1503 Arabic and 1874 English videos. These videos need to be aligned in order to compare their contents, that is why we propose several methods to make them comparable. Then the best one is selected to align them and to constitute the data-set necessary for the fine-grained sentiment analysis

Extractive Text-Based Summarization of Arabic videos: Issues, Approaches and Evaluations

International audienceIn this paper, we present and evaluate a method for extractive text-based summarization of Arabic videos. The algorithm is proposed in the scope of the AMIS project that aims at helping a user to understand videos given in a foreign language (Arabic). For that, the project proposes several strategies to translate and summarize the videos. One of them consists in transcribing the Ara-bic videos, summarizing the transcriptions, and translating the summary. In this paper we describe the video corpus that was collected from YouTube and present and evaluate the transcription-summarization part of this strategy. Moreover, we present the Automatic Speech Recognition (ASR) system used to transcribe the videos, and show how we adapted this system to the Algerian dialect. Then, we describe how we automatically segment into sentences the sequence of words provided by the ASR system, and how we summarize the obtained sequence of sentences. We evaluate objectively and subjectively our approach. Results show that the ASR system performs well in terms of Word Error Rate on MSA, but needs to be adapted for dealing with Algerian dialect data. The subjective evaluation shows the same behaviour than ASR: transcriptions for videos containing dialectal data were better scored than videos containing only MSA data. However, summaries based on transcriptions are not as well rated, even when transcriptions are better rated. Last, the study shows that features, such as the lengths of transcriptions and summaries, and the subjective score of transcriptions, explain only 31% of the subjective score of summaries

PADIC: extension and new experiments

International audiencePADIC is a multidialectal parallel Arabic corpus. It was composed initially by five Arabic dialects, three from the Maghreb and two from the Middle East, in addition to standard Arabic. In this paper, we present an augmented version of PADIC with a Moroccan dialect. We give also an evaluation, using the σ–index, of the computerization level of the Arabic dialects present in PADIC which reveals that these languages are really under-resourced. Several experiments in machine translation, in both sides between all the combinations of language pairs, are discussed too. For each language, we interpolated the corresponding Language Model (LM) with a large Arabic corpus based LM. The results show that this interpolation is in some cases without effect on the performances of translation systems and in others is rather penalizing

PADIC: extension and new experiments

International audiencePADIC is a multidialectal parallel Arabic corpus. It was composed initially by five Arabic dialects, three from the Maghreb and two from the Middle East, in addition to standard Arabic. In this paper, we present an augmented version of PADIC with a Moroccan dialect. We give also an evaluation, using the σ–index, of the computerization level of the Arabic dialects present in PADIC which reveals that these languages are really under-resourced. Several experiments in machine translation, in both sides between all the combinations of language pairs, are discussed too. For each language, we interpolated the corresponding Language Model (LM) with a large Arabic corpus based LM. The results show that this interpolation is in some cases without effect on the performances of translation systems and in others is rather penalizing

Constitution d'un corpus de la langue Arabe à partir du Web

International audienceLa toile est une source intarissable de données textuelles. Ces dernières années la communauté travaillant sur les différents aspects de la langue s'est tournée vers le web afin de bénéficier de cette masse impressionnante d'informations. Cet article décrit un outil de construction de corpus pour l'Arabe. Il permet de recueillir automatiquement une liste de sites dédiés à la langue Arabe. Ensuite le contenu de ces sites est extrait et est normalisé. Le corpus ainsi constitué peut être utilisé dans diverses applications de traitement du langage naturel et plus particulièrement dans le calcul de modèles de langage statistiques

Constitution d'un corpus de la langue Arabe à partir du Web

International audienceLa toile est une source intarissable de données textuelles. Ces dernières années la communauté travaillant sur les différents aspects de la langue s'est tournée vers le web afin de bénéficier de cette masse impressionnante d'informations. Cet article décrit un outil de construction de corpus pour l'Arabe. Il permet de recueillir automatiquement une liste de sites dédiés à la langue Arabe. Ensuite le contenu de ces sites est extrait et est normalisé. Le corpus ainsi constitué peut être utilisé dans diverses applications de traitement du langage naturel et plus particulièrement dans le calcul de modèles de langage statistiques

A COMPARATIVE STUDY BETWEEN POLYCLASS AND MULTICLASS LANGUAGE MODELS

International audienceIn this work, we introduce the concept of Multiclass for language modeling and we compare it to the Polyclass model. The originality of the Multiclass is its capability to parse a string of classes/tags into variable length independent sequences. A few experimental tests were carried out on a class corpus extracted from the French « Le Monde » word corpus labeled automatically. This corpus contains a set of 43 million of words. In our experiments, Multiclass outperform first-order Polyclass but are slightly outperformed by second-order Polyclass