Investigating Range-Equalizing Bias in Mean Opinion Score Ratings of Synthesized Speech

17 May 2023  ·  Erica Cooper, Junichi Yamagishi ·

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.

PDF Abstract
No code implementations yet. Submit your code now

Tasks


Datasets


  Add Datasets introduced or used in this paper

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods