Aviation English (AE) is under scrutiny due to miscommunication between international pilots and controllers. To enhance public safety, since 2011, aviation professionals must prove technical and practical English proficiency. Previous studies measure AE speech accuracy by task performance and repeated elements (Barshi and Healy, 2011), and speech comprehensibility using native speaker judgments (Farris et al., 2008). The current study develops a quantifiable index for evaluating AE production based on prosody. Reasonably fluent prosody is critical to language comprehensibility generally, but since AE has no predictable intonation due to signal limitations, lack of function words, standard phraseology and rapid speech rate, we are specifically developing a rhythm profile of Native Speaker AE (NSAE) to evaluate Non-native Speaker AE production and model training methods for different first language (L1) prosodic types. We are training a speech aligner on tapes of US controllers to calculate a baseline for American NSAE. Our index will be generated using known metrics such as delta-V/C, %V (Ramus, 2000), PVI (Low et al., 2000), and varcoV/C (Dellwo, 2006). Since AE is derived from “stress-timed” English to be standardized and predictable, we predict that AE will exhibit a rhythmic signature comparable not only to English but to “syllable-timed” languages.