Methodology for Sound Quality Metric Development

Many individual technical descriptors exist to quantify and describe different kinds of acoustic phenomena. However, each only describes the technical aspects of a sound itself without considering any additional non-acoustic context. Human perception is greatly informed by this context. For example, humans have different expectations for the sound of an electric razor than they do for an internal combustion engine, despite both objects being able to be described by sound pressure level or a measure of roughness. No single technical descriptor alone works in all contexts as a gold standard that objectively determines whether a sound is “good.” Jury tests, however, are a great aid in gaining a measure of this context. When seeking to develop a meaningful quality index for the sounds of a device, it is often necessary to combine the perceptive information from the results of a jury test alongside one or more technical descriptors. The combination of perceptive data and technical descriptors ultimately forms a calculation rule, called a metric, which typically provides a single value that accurately characterizes how a human will perceive a sound. This paper describes a methodology for creating metrics by first defining a context in which to analyze a set of sounds. Appropriate data acquisition methods are discussed, alongside jury test creation and administration. Lastly, statistical methods are described for use in jury test postprocessing and the selection of technical descriptors for use in the development of a metric.