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An Affect-based approach for QoE evaluation in VoIP Systems. Abhishek Bhattacharya, Zhenyu Yang & Deng Pan IEEE Global Communications Conference (GLOBECOM) 2011 5 – 9 December , Houston, TX. Roadmap. Introduction Problem Current Solutions Affect-based Approach Experimental Setup
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An Affect-based approach for QoE evaluation in VoIP Systems Abhishek Bhattacharya, Zhenyu Yang & Deng Pan IEEE Global Communications Conference (GLOBECOM) 2011 5 – 9 December , Houston, TX
Roadmap • Introduction • Problem • Current Solutions • Affect-based Approach • Experimental Setup • Results • Summary
Introduction: VoIP • What is VoIP Quality? • Signal -- How good you hear? How good you are heard? • Network – Packets travelling through good paths? • Anything more?
Introduction: QoE assessment • Why is Quality of Experience important? • better perceptual experience • seamless interactivity • high responsiveness • Why is Quality of Experience Assessment important? • monitoring • management
Roadmap • Introduction • Problem • Current Solutions • Affect-based Approach • Experimental Setup • Results • Summary
Problem: What is QoE? • User’s satisfaction about a multimedia service • How to estimate the QoE of VoIP implicitly and non-intrusively ?
Roadmap • Introduction • Problem • Current Solutions • Affect-based Approach • Experimental Setup • Results • Summary
Current Solutions: QoS-based • QoS-based : delay, loss-rate, jitter, etc. • Issues: Which QoS metric is most influential on QoE? • Data rate? Loss? Delay? Jitter? Combination of them? • Modeling from QoS to QoE cannot cover all cognitive • factors
Current Solutions: User Feedback • User Feedback : Mean Opinion Score (MOS) • Issues: Intrusiveness, Scalability, High Cognitive resource • overhead !
Current Solutions: Media Quality • Media Quality Analysis : Signal Distortion Models such as • SNR, Perceptual Evaluation of Speech Quality (PESQ) • Issues: Double-ended techniques are not practical in most cases • Fails to consider various listening levels, side-tone/talk • echo, conversational delay/interaction
Roadmap • Introduction • Problem • Current Solutions • Affect-based Approach • Experimental Setup • Results • Summary
Affect-based Approach • Affective Computing deals with the analysis of human • emotional variables revealed during various human- • computer interaction • Affect has been shown to have strong association with user • experience regarding interest, satisfaction, motivation, • performance, and perception.
Affect-based Approach: Hypothesis • We propose a new affect-based methodology of QoE evaluation in voice communication systems • Advantages: Implicit, Non-intrusive, and Low overhead • The user perception of voice communication quality is correlated to his/her affective response, which will vary across networking conditions.
Affect-based Approach: Framework Acoustic Feature Extraction Acoustic Feature Selection Acoustic Classifier Lexical Feature Extraction Lexical Classifier Audio Signal Automatic Speech Recognition QoE Prediction Discourse Feature Extraction Discourse Classifier
Affect-based Approach: Acoustic • Extracted 22 acoustic features derived from turn-level statistical functional and transformations in fundamental frequency(F0), energy, duration, and formants. • Classified in 4 types: • Base: includes all 22 attributes • f10: 10 best attribute features using leave-one-out • f15: 15 best attribute features using leave-one-out • PCA: Principal Component Analysis
Affect-based Approach: Lexical • Modeling salient or distinctive words (e.g., “can’t”, “damn”, “great”, “bad”) for various expressions by the notion of mutual information to establish the correlation between words and different QoE levels. Pardon me! I’m not able to hear you! Damn it! I couldn't get your words!
Affect-based Approach: Discourse Hello !! Hello ! R u there ? R u there ? • Trouble in communication ? • Repetitions • 1-word to 5-word repetitions with increased weightage
Roadmap • Introduction • Problem • Current Solutions • Affect-based Approach • Experimental Setup • Results • Summary
Experimental Setup Linux bridge with Dummynet • Modeled the network dynamics using delay. Loss-rate, bandwidth • and divided into 5 classes i.e., C1, C2, C3, C4, C5. • We employed a trichotomous or 3-point scale decision of • perceptual quality levels: “Good", “Average", and “Bad"
Roadmap • Introduction • Problem • Current Solutions • Affect-based Approach • Experimental Setup • Results • Summary
Roadmap • Introduction • Problem • Current Solutions • Affect-based Approach • Experimental Setup • Results • Summary
Summary • Our work represents an important step towards QoE of future • generation of communication systems (media rich, immersive) • Studying influence of other affective cues (i.e., laughter, sigh) • and discourse features (i.e., rephrase, reject, ask-over) • Applying Internet traces to simulate more realistic scenarios
Thank You........ Questions ??? to abhat002@cis.fiu.edu