MUSHRA stands for MUltiple Stimuli with Hidden Reference and Anchor and is a methodology for subjective evaluation of audio quality, to evaluate the perceived quality of the output from lossy audio compression algorithms. It is defined by ITU-R recommendation BS.1534-3. The MUSHRA methodology is recommended for assessing "intermediate audio quality". For very small audio impairments, Recommendation ITU-R BS.1116-2 (ABC/HR) is recommended instead.
The main advantage over the Mean Opinion Score (MOS) methodology (which serves a similar purpose) is that it requires fewer participants to obtain statistically significant results. This is because all codecs are presented at the same time, on the same samples, so that a paired t-test can be used for statistical analysis. Also, the 0-100 scale makes it possible to rate very small differences. In MUSHRA, the listener is presented with the reference (labeled as such), a certain number of test samples, a hidden version of the reference and one or more anchors. The recommendation specifies that one anchor must be a 3.5 kHz low-pass version of the reference. The purpose of the anchor(s) is to make the scale be closer to an "absolute scale", making sure that minor artifacts are not rated as having very bad quality.
- RateIt: A GUI for performing MUSHRA experiments
- MUSHRAM - A Matlab interface for MUSHRA listening tests
- A Max/MSP interface for MUSHRA listening tests
- A Browser Based Audio Evaluation Tool, for running many different tests including MUSHRA - No coding needed
- mushraJS+Server: based on mushraJS with mochiweb server, which is erlang web server
|This computing article is a stub. You can help Wikipedia by expanding it.|
|This signal processing-related article is a stub. You can help Wikipedia by expanding it.|