# Voice Maps as a Tool for Understanding and Dealing with Variability in the Voice
### Voice Map Definitions  
Any map needs a coordinate system. For voice maps, we propose that the coordinate system be called the _voice field_, with fundamental frequency \(f_{\rm o}\) given in semitones on the horizontal axis, and sound pressure given as the sound pressure level SPL (dB) on the vertical axis [13] (Chapter 1). (The German term _Stimmfeld_ has sometimes been used as a name for the voice range profile proper, rather than for its coordinate system. We hope that this will not cause confusion.) Over this plane, we can arrange values derived from a scalar property of the sound, according to the \(f_{\rm o}\) and SPL at any given moment. Such a representation is often called a _scalar field_. On a topographical map of a geographical area, the scalar value is often the height above sea level, encoded using a colour scale. Conventionally, the metric values are averaged in bins or \"cells\" that are one semitone wide and one decibel high. In effect, the observations in each and every cell will have a statistical distribution, with a mean, standard deviation, etc. On a voice map, it is usually the per-cell distribution _mean_ value that is encoded on the colour scale. The graphics are plotted in real time, so both the clinician and the patient can see the \"land\" on the map growing as the patient's voice is exercised over the range of the task. In practice, we are not content to measure just one metric; rather, several selected physical entities are measured many times per second during phonation, each using a well-defined metric. Each metric is then represented on a separate \"layer\" of the voice map. Although many voice metrics will be mentioned in this article, it is not the details of how they are defined, measured, or interpreted that is at issue, but rather how they are collected, coordinated, and presented. Fundamentally, semitones and decibels are both logarithmic representations, and in most cases, a logarithmic representation also of each metric is preferred [13] (pp. 40-70). Log-log-log systems have useful mathematical properties, such as invariance under scaling, and they have a practical similarity to human sensory perception scales. They also raise mathematical issues, such as how to define a standard deviation when observations are made on a log scale, but those issues will be considered to be out of scope for this article. In Figure 1, we see maps of four colour-coded metrics of the EGG and audio signals, all from the same recording of the same person, a vocally healthy male amateur singer singing in the modal register (M1) only [14]. The task here was to sing soft-loud-soft on an /a/ vowel only, over a limited range. Without going into the specifics of each metric [15] it is clear that all of them vary over this range: considerably so in the vertical direction (which represents sound level) and to some extent also horizontally (which represents the fundamental frequency \(f_{\rm o}\)). It is also clear that while the four metrics exhibit some co-variation, they report on different aspects of this voice. This example was chosen for its relative simplicity in its trends over SPL and \(f_{\rm o}\). Typically, a map over the full range of a voice would be more complex. Imagine now that any of the maps in Figure 1 is a topographical map of a geographical area, with height mapped to colour. An intriguing thing happens when we ask the participant to repeat the same task many times: the features on the map gradually become clearer and smoother; but they do not change, so long as the voice remains the same. The \"landscape\" that is being \"surveyed\" only becomes more well-defined. This means that the topographical features on the map reflect such properties of voice production that are specific, not to sounds being produced in the moment, but to physiological aspects of the mechanism that is producing them. The maps do not just show pretty colours: each metric represents hard facts about what is going on inside the body and in the air.