Application of Just-Noticeable Difference in Quality as Environment Suitability Test for Crowdsourcing Speech Quality Assessment Task
This addresses the need for more reliable speech quality assessments in crowdsourcing, though it is incremental as it builds on existing ITU-T standards and preliminary work.
The paper tackled the problem of unreliable speech quality assessments in crowdsourcing due to varying listener environments and devices by proposing a Just-Noticeable Difference of Quality (JNDQ) test as a screening method, finding that environment and device significantly affect JNDQ thresholds and suggesting a minimum threshold for screening.
Crowdsourcing micro-task platforms facilitate subjective media quality assessment by providing access to a highly scale-able, geographically distributed and demographically diverse pool of crowd workers. Those workers participate in the experiment remotely from their own working environment, using their own hardware. In the case of speech quality assessment, preliminary work showed that environmental noise at the listener's side and the listening device (loudspeaker or headphone) significantly affect perceived quality, and consequently the reliability and validity of subjective ratings. As a consequence, ITU-T Rec. P.808 specifies requirements for the listening environment of crowd workers when assessing speech quality. In this paper, we propose a new Just Noticeable Difference of Quality (JNDQ) test as a remote screening method for assessing the suitability of the work environment for participating in speech quality assessment tasks. In a laboratory experiment, participants performed this JNDQ test with different listening devices in different listening environments, including a silent room according to ITU-T Rec. P.800 and a simulated background noise scenario. Results show a significant impact of the environment and the listening device on the JNDQ threshold. Thus, the combination of listening device and background noise needs to be screened in a crowdsourcing speech quality test. We propose a minimum threshold of our JNDQ test as an easily applicable screening method for this purpose.