PROJECT TITLE :

Context-Sensitive Learning for Enhanced Audiovisual Emotion Classification

ABSTRACT:

Human emotional expression tends to evolve during a structured manner in the sense that certain emotional evolution patterns, i.e., anger to anger, are a lot of probable than others, e.g., anger to happiness. Furthermore, the perception of an emotional display will be tormented by recent emotional displays. Therefore, the emotional content of past and future observations could provide relevant temporal context when classifying the emotional content of an observation. During this work, we have a tendency to specialise in audio-visual recognition of the emotional content of improvised emotional interactions at the utterance level. We tend to examine context-sensitive schemes for emotion recognition within a multimodal, hierarchical approach: bidirectional Long Short-Term Memory (BLSTM) neural networks, hierarchical Hidden Markov Model classifiers (HMMs), and hybrid HMM/BLSTM classifiers are thought of for modeling emotion evolution inside an utterance and between utterances over the course of a dialog. Overall, our experimental results indicate that incorporating long-term temporal context is beneficial for emotion recognition systems that encounter a selection of emotional manifestations. Context-sensitive approaches outperform those without context for classification tasks like discrimination between valence levels or between clusters within the valence-activation area. The analysis of emotional transitions in our database sheds light into the flow of affective expressions, revealing probably useful patterns.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE :Synthesis and Analysis of Context-Sensitive LanguagesABSTRACT:Context-sensitive languages are sometimes omitted in undergraduate textbooks on Theory of Computation or studied only from structural purpose of read
PROJECT TITLE :Network Traffic Classification Using Correlation Information - 2013ABSTRACT:Traffic classification has wide applications in network management, from security monitoring to quality of service measurements. Recent
PROJECT TITLE :The Generalization Ability of Online Algorithms for Dependent Data - 2013ABSTRACT:We study the generalization performance of online learning algorithms trained on samples coming from a dependent source of data.
PROJECT TITLE :Learning, Retention, and Slacking: A Model of the Dynamics of Recovery in Robot TherapyABSTRACT:Quantitative descriptions of the process of recovery of motor functions in impaired subjects during robot-assisted
ABSTRACT:Both the American Heart Association and the VA/DoD endorse upper-extremity robot-mediated rehabilitation therapy for stroke care. However, we do not know yet how to optimize therapy for a particular patient's needs. Here,

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry