# Voice Maps as a Tool for Understanding and Dealing with Variability in the Voice
## 2 Aspects of Variability in Voice
### The Independent Variables: SPL and \(f_{\rm o}\)  
In voice signals, SPL and \(f_{\rm o}\) are the two variables that are the most readily observable, while at the same time being under the volitional control of the speaker or singer. Controlling SPL and \(f_{\rm o}\) adequately is essential, where \"adequately\" implies different criteria for different styles of speech and of singing. This degree of control makes SPL and \(f_{\rm o}\) useableas the two primary _independent_ variables for voice mapping, i.e., for observing a dependent metric over a relevant range.  
As noted above, many quantitative studies of the voice, including those that use the VRP, take \(f_{\rm o}\) and SPL as the dependent variables, and in such cases, the primary interest lies in the observed distribution shapes and statistics of those two variables. In voice mapping, \(f_{\rm o}\) and SPL are instead seen as control parameters, i.e., _in_dependent variables. The distributions of these two variables are then important only for ensuring that an adequate number of observations of the metric(s) under study are collected at all relevant fundamental frequencies and voice sound levels. In practice, this means that the total time spent phonating in any particular cell on the map is not important. Further on, we will elaborate on the criteria for an \"adequate number of observations\".  
In speech, \(f_{\rm o}\) and SPL co-vary mainly because (1) both increase with subglottal pressure, and (2) acoustically, the voice becomes a more efficient sound source as \(f_{\rm o}\) increases [26]. This co-variation is so familiar that we hardly think about it. It is also the reason for the generally upward-slanting, oblique appearance of phonated areas in voice maps and VRPs. In a singer, the softest usable performance voice at high pitch can even have a higher sound level than the loudest possible voice at low pitch [5] (p. 43). Perceptually, the SPL is much more a correlate of _distance_ than of vocal effort [27]. The SPL depends also on the size of the mouth opening by some \(\pm 5\) dB [28], and there are other not-so-direct relationships between vocal effort and vocal tract articulation that play into the co-variation of \(f_{\rm o}\) and SPL as well. It would seem, then, that SPL is not an ideal metric to use as a coordinate on a voice map.  
Nonetheless, we normally employ the SPL as an indirect proxy for a more informative metric: the acoustical power (in watts) radiated by a voice, which is hard to measure directly. The source power can however be estimated from the SPL, if we account carefully for the mouth-to-microphone distance. There is an intuitive _optical_ analogy here: the radiated acoustic power is analogous to the actual height of a person, while the SPL corresponds to the imaged full-figure height that one measures on a photograph. The latter decreases with distance to the camera, and increases with the magnification of the lens, which corresponds to the audio gain. One of several reasons for choosing a standard microphone distance of 0.3 m is that, at this distance, the sound pressure level in dB and the power level in dB radiated by the mouth, which does not depend on the distance, happen to be approximately the same [29]. Because many voice metrics are highly dependent on the voice output power, accurate calibration of the SPL is crucial when making voice maps that are to be compared to each other. As for the fundamental frequency, fortunately, the temporal precision and stability of digital audio interfaces is very high, and hence calibration of \(f_{\rm o}\) measurements is rarely necessary, so long as all relevant sampling rates are properly matched.  
Once a voice map has been made, it is static. The temporal context is discarded, which reinforces the distinction between voice (the machine) and speech (its output). By design, then, voice maps are helpful for analyzing voices rather than speech.