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Investigating Range-Equalizing Bias in Mean Opinion Score Ratings of Synthesized Speech
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Mean Opinion Score (MOS) is a popular measure for evaluating synthesized speech. However, the scores obtained in MOS tests are heavily dependent upon many contextual factors. One such factor is the overall range of quality of the samples presented in the test -- listeners tend to try to use the entire range of scoring options available to them regardless of this, a phenomenon which is known as range-equalizing bias. In this paper, we systematically investigate the effects of range-equalizing bias on MOS tests for synthesized speech by conducting a series of listening tests in which we progressively "zoom in" on a smaller number of systems in the higher-quality range. This allows us to better understand and quantify the effects of range-equalizing bias in MOS tests.
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Cited by 1 Pith paper
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Rethinking MUSHRA: Addressing Modern Challenges in Text-to-Speech Evaluation
MUSHRA's reliance on a human reference biases ratings of modern TTS systems, and removing the reference or using detailed scoring guidelines produces scores closer to CMOS preferences.
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