提出更贴近真实评分行为的多媒体质量评分方差模型
A Mixed-Behavior Vote Model for Multimedia Subjective Quality Votes, Means, and Variances
- 构建了单峰方差区域UVR，更好描述真实评分波动
- 提出新模型使方差与平均分关系始终在合理范围内
- 可生成符合实际的评分数据，适合质量评估研究者
主观评分的方差与均值（或MOS）关系已有深入研究，此前已定义数学上可接受的方差区域。本文提出一个简化后的可接受方差区域——单峰方差区域（UVR），能更准确地描述多媒体主观评分的实际行为。现有研究常将评分方差建模为抛物线形式，但实践中该模型常超出可接受区域。我们提出替代方案，确保方差与MOS的关系始终在可接受范围内。此外，我们设计了一个参数化随机过程，融合多种投票机制，在任意给定MOS下生成符合UVR的现实评分方差范围。该过程基于大量主观实验中观察到的投票行为，具有良好的现实依据。通过从主观实验中建模评分方差，该模型为实验中的评分行为提供了额外可解释的洞察。我们在16个涵盖语音、图像和视频质量的主观测试数据集上展示了实例结果。
原文摘要 · Abstract (English)
The relationship between subjective test vote variance and vote mean (or MOS) is well-studied, and the mathematically admissible vote variance region has been previously defined. We propose a reduced admissible variance region called the Unimodal Variance Region (UVR) that better describes real subjective rating behavior of multimedia. Further, subjective vote variance is often modeled as parabolic. We explain that, in practice, the parabolic model often violates the admissible region in the variance vs. MOS plane and we propose alternatives that respect the admissible region. We also present a parametrized random process to model votes that mixes voting processes and produces a realistic range of vote variances within the UVR at any desired MOS. This process was inspired by and comports with voting behavior that is observed in many subjective tests. By modeling vote variance from a subjective experiment, this vote model offers additional interpretable insights into voting behavior observed in a given experiment. We present example results from 16 datasets spanning speech, image, and video subjective quality experiments.
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