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    This study introduces a new model to predict video streaming quality. It accurately forecasts viewer experience by analyzing video content and viewer memory, improving quality control for services like Netflix.

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    Area of Science:

    • Multimedia streaming quality assessment
    • Human-computer interaction in media consumption

    Background:

    • Adaptive video streaming services face challenges from fluctuating network conditions, causing rebuffering and bitrate changes.
    • These issues degrade the viewer's quality of experience (QoE) and can lead to subscriber churn.
    • Existing QoE models often lack accuracy due to their reliance on simple global features and failure to account for human perception.

    Purpose of the Study:

    • To develop an accurate predictor of instantaneous subjective Quality of Experience (QoE) for adaptive video streaming.
    • To enable more efficient design of quality-control protocols for major media services.
    • To address limitations of existing models by incorporating perceptual and cognitive factors.

    Main Methods:

    • Developed the time-varying QoE Indexer, a novel QoE evaluator.
    • Analyzed spatial and temporal video content, and client-side data buffer status.
    • Incorporated human cognitive factors like memory and recency into the prediction model.

    Main Results:

    • The QoE Indexer predicts continuous-time quality scores that align well with human opinion scores.
    • The model effectively accounts for interactions between stalling events and video content.
    • Demonstrated standout QoE prediction performance across three diverse video databases.

    Conclusions:

    • The proposed time-varying QoE Indexer offers a significant advancement in predicting viewer experience during video streaming.
    • This model provides a more nuanced understanding of QoE by integrating content analysis, network conditions, and human perception.
    • The findings support the development of enhanced quality-control strategies for over-the-top streaming platforms.