CAPQ-FAST: Content-Adaptive Perceived Quality Assessment for Faster Audiovisual Playback

2026-09-03

AI Summary

研究通过主观实验分析了不同媒体内容在加速播放下的感知质量，并提出了一种基于内容特性的自适应感知质量评估模型CAPQ-FAST。

Abstract

Faster playback has become a common feature in modern online audiovisual services, allowing users to consume content in less time while still maintaining a coherent viewing experience. However, different modalities of media content, such as video, audio (including speech and music), and audiovisual, exhibit varying requirements for understandability and information integrity under faster playback. These differences lead to noticeable variations in perceived quality depending on the content type. Nevertheless, users' perceived quality at different playback speeds remains insufficiently investigated. To address this gap, this paper conducts a series of subjective experiments to analyze the relationship between playback speed and perceived quality for video, audio, and audiovisual content. Content-specific intrinsic features are extracted to capture temporal dynamics, including temporal information (TI) for video, words per minute (WPM) for speech, and beats per minute (BPM) for music. Predictive models of perceived quality under faster playback are then developed separately for video, speech, and music. By integrating these models, a unified content-adaptive perceived quality assessment model (CAPQ-FAST) is proposed for faster audiovisual playback. Experimental results demonstrate that the proposed model effectively predicts perceived quality under different playback speeds. This model can help service providers better understand users' viewing intentions and perceptual experiences under faster playback, thereby enabling more adaptive personalized recommendations and playback control to enhance user experience adaptability.

Problem

• perceived quality
• playback speed
• media content

Innovation

• Content-Adaptive
• Perceived Quality Assessment
• Faster Playback
• Temporal Dynamics
• Unified Model