# Voice Maps as a Tool for Understanding and Dealing with Variability in the Voice
### The Voice Range Profile  
A special case of voice maps has been around for a very long time, namely, the voice range profile (VRP; also known as the phonetogram) [4; 5] (Chapter 3). A VRP is a voice map that is acquired in order to determine the widest possible range that a person's voice can produce: softest, loudest, lowest, and highest. In the VRP paradigm,\(f_{\text{o}}\) and SPL are dependent variables, and changes in their distribution statistics (minimum, mean, maximum, range etc.) are hypothesized to be related to the outcome of a clinical intervention or training. Typically, one then assesses mainly the contour or \"coastline\" of this \"reachable region\", and the metric that one observes is simply the presence or absence of phonation. In many cases, a vocal problem will result in a reduced range, and there is a large body of literature that is concerned with eliciting and interpreting such contours. However, reliable elicitation of the extremes takes a fair amount of time in the clinic. Furthermore, using one's voice at its extremes is in itself an acquired skill, which can increase even during one session, especially with the interactive real-time feedback afforded by modern systems. Clinicians are sometimes sceptical of the VRP, because of the time-with-patient and the operator training that it requires. Close adherence to a standard protocol is necessary for good reproducibility [6; 7; 8]. Cutting corners will incur confounding variability and inconsistent results. On the other hand, many clinical assessments do not require the full voice range to be mapped. For instance, if only the contour is sought, a shorter protocol may suffice [9]. In daily speech, the voice traverses only a very small part of the full range. Such a range can be quantified by the speech range profile (SRP) [10], so if the main interest is to assess ecologically valid productions in the speech range only, then reading a text for a few minutes may be enough [11]. As far back as 1988 [12], author [PERSON] and co-workers realized that a signal-processing system that extracts SPL and \(f_{\text{o}}\) for making VRPs can also extract other metrics at the same time, and render them in that frame of reference, using a gray scale or colour mapping. This was the birth of voice-mapping, if under a different name. It was commercialized by author [PERSON] and attracted a substantial user base among speech-language pathologists. It also inspired author [PERSON] to include the VRP in the voice analysis software that he was developing in the 1990s, and which has seen extensive use in Swedish voice clinics. In 2011, [PERSON] and students began exploring how the acoustic and electroglottographic (EGG) signals might be combined so as to give a more complete picture of how the voice operates over its range, using non-invasive measurements. This ongoing work has persuaded both of us that the variability in voices needs more research attention than it has so far received, which is why we have written this paper. Specifically, the _object_ of the present article is the challenge presented by variability in the human voice to the task of making meaningful measurements on meaningful scales. The primary _purpose_ of the article is to illustrate how the voice mapping paradigm, by coordinating voice measurements in a non-temporal frame, can rise to that challenge. The _subject of research_ is the use of two-dimensional scalar fields to represent variations in voice metrics as functions of two primary independent variables: fundamental frequency (\(f_{\rm o}\)) and voice sound pressure level (SPL).