A First Summarization System of a Video in a Target Language

International audienceIn this paper, we present the first results of the project AMIS (Access Multilingual Information opinionS) funded by Chist-Era. The main goal of this project is to understand the content of a video in a foreign language. In this work, we consider the understanding process, such as the aptitude to capture the most important ideas contained in a media expressed in a foreign language. In other words, the understanding will be approached by the global meaning of the content of a support and not by the meaning of each fragment of a video. Several stumbling points remain before reaching the fixed goal. They concern the following aspects: Video summarization, Speech recognition, Machine translation and Speech segmentation. All these issues will be discussed and the methods used to develop each of these components will be presented. A first implementation is achieved and each component of this system is evaluated on a representative test data. We propose also a protocol for a global subjective evaluation of AMIS

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

Evaluation of Improved Components of AMIS Project for Speech Recognition, Machine Translation and Video/Audio/Text Summarization

International audienceTo evaluate a system that automatically summarizes video files (image and audio) and text, how the system works, and the quality of the results should be considered. With this objective, the authors have performed two types of evaluation: objective and subjective. The actual assessment is performed mainly automatically, while the individual assessment is based directly on the opinion of people, who evaluate the system by answering a set of questions, which are then processed to obtain the targeted conclusions. One of the purposes of the described research is to try to narrow the space of possible summarization scenarios. Meanwhile, in the light of individual results obtained, the researchers cannot unambiguously indicate one single scenario, recommended as the only one for further development. However, the researchers can state with certainty that the new development of scene 1, which has received many negative evaluations among professionals, should be discontinued. Considering the results of the set of questions about the quality of the complete system, the end-users have evaluated the scenario 3, and they think that the quality is excellent, obtaining results over 70% on a scale of 0 to 100

A First Summarization System of a Video in a Target Language

International audienceIn this paper, we present the first results of the project AMIS (Access Multilingual Information opinionS) funded by Chist-Era. The main goal of this project is to understand the content of a video in a foreign language. In this work, we consider the understanding process, such as the aptitude to capture the most important ideas contained in a media expressed in a foreign language. In other words, the understanding will be approached by the global meaning of the content of a support and not by the meaning of each fragment of a video. Several stumbling points remain before reaching the fixed goal. They concern the following aspects: Video summarization, Speech recognition, Machine translation and Speech segmentation. All these issues will be discussed and the methods used to develop each of these components will be presented. A first implementation is achieved and each component of this system is evaluated on a representative test data. We propose also a protocol for a global subjective evaluation of AMIS