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Detecting emotions in the context of automated call center services can be helpful for following the evolution of the human-computer dialogs, enabling dynamic modification of the dialog strategies and influencing the final outcome. The emotion detection work reported here is a part of larger study aiming to model user behavior in real interactions. We make(More)
This paper addresses the issue of automatic emotion recognition in speech. We focus on a type of emotional manifestation which has been rarely studied in speech processing: fear-type emotions occurring during abnormal situations (here, unplanned events where human life is threatened). This study is dedicated to a new application in emotion recognition –(More)
Recent work on emotional speech processing has demonstrated the interest to consider the information conveyed by the emotional component in speech to enhance the understanding of human behaviors. But to date, there has been little integration of emotion detection systems in effective applications. The present research focuses on the development of a(More)
The present paper aims at filling the lack that currently exists with respect to databases containing emotional manifestations. Emotions, such as strong emotions, are indeed difficult to collect in real-life. They occur during contexts, which are generally unpredictable, and some of them such as anger are less frequent in public life than in private. Even(More)
This paper reports on an analysis of prosodic cues for emotion characterization in 100 natural spoken dialogs recorded at a telephone customer service center. The corpus annotated with task-dependent emotion tags which were validated by a perceptual test. Two F0 range parameters , one at the sentence level and the other at the sub-segment level, emerge as(More)
The present research focuses on analyzing and detecting emotions in speech as revealed by task-dependent spoken dialogs corpora. Previously, we have conducted several experiments on a real-life corpus in order to develop a reliable annotation method and to detect lexical and prosodic cues correlated to the main emotion class. In this paper we evaluate both(More)
It is widely acknowledged that human listeners significantly outperform machines when it comes to transcribing speech. This paper presents a paradigm for perceptual experiments that aims to increase our understanding of human and automatic speech recognition errors. The role of the context length is investigated through perceptual recovery of small(More)
This paper deals with the overview of the methods in perceptual language identification and the suggestion of a new approach based on a two-step methodology integrating to perception " genetic " considerations and resulting into the modeling of perceptually identified discriminative cues. The first study reported here concerns experimental designs for(More)
This paper deals with perceptual identification and differentiation of five Romance languages, namely French, Italian, Spanish, Portuguese and Romanian. Previous studies have investigated human capability to identify spoken samples in unknown languages after a relatively brief exposure. Moreover, they have shown that subjects use perceptual categories and(More)