Ioana Vasilescu

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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)
Automatic emotion detection is potentially important for customer care in the context of call center services. A major difficulty is that the expression of emotion is quite complex in the context of agent-client dialogs. Due to unstated rules of politeness it is common to have shaded emotions, in which the interlocutors attempt to limit their internal(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)
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)
This paper addresses the question of perceptual detection and prosodic cues analysis of emotional behavior in a spontaneous speech corpus of real Human-Human dialogs. Detecting real emotions should be a clear focus for research on modeling human dialog, as it could help with analyzing the evolution of the dialog. Our aims are to define appropriate emotions(More)
In this paper, we present a Conditional Random Field based approach for automatic detection of edit disfluencies in a conversational telephone corpus in French. We define dis-fluency patterns using both linguistic and acoustic features to perform disfluency detection. Two related tasks are considered : the first task aims at detecting the disfluent speech(More)
A disposable amperometric biosensor was developed for the detection of total polyphenolic compounds from tea infusions. The biosensor was designed by modifying the surface of a carbon screen-printed electrode with platinum nanoparticles and reduced graphene oxide, followed by the laccase drop-casting and stabilization in neutralised 1% Nafion solution. The(More)