Week 8: More Processing Necessary (or, “Always Check Your Assumptions”)
May 16, 2025
Hello all! This week, Dr. Newman and I had an important realization about my results. We were looking at how different “r” types compared to one another, and saw that “Nurse” tokens were overall more rhotic than “Onset” tokens. This doesn’t make much sense—as I mentioned before, it is usually assumed that “Onset” tokens should be the most rhotic and never weaken, because people don’t typically observe dropped “r”s at the start of words. We had noticed this contradiction already, and chalked it up to an issue with measuring the “Onset” tokens.
However, this actually seems to be part of a deeper problem with our analysis. This entire time that we’ve been comparing the different types of token, we have been making the underlying assumption that the F3-F2 measurement means the same thing for all types. But really, it doesn’t correctly represent the amount that the “r” was weakened. For example, if a “Shwar” token was fully weakened, as in a British accent, it would become the vowel /ə/—found in General American English at the ends of “arena” and “Laura”—while if a “Nurse” token was fully weakened, it would become /ɜ/ (not otherwise found in General American). Because the different “r” types weaken to become different vowels, comparing them directly with each other is inaccurate. Instead, each should be compared with its corresponding vowel to determine how weakened it has become.
To this end, I now have to go back through all of the recordings and measure F3-F2, our main metric of rhoticity, for all of the normal vowels like /ə/ and /ɜ/. This way, if some vowels sound more rhotic, we can correct for that in our analysis of “r”. On the bright side, this will also be very useful data to have for future study by myself or others. On the dark side, running FastTrack on the hundreds of recordings will take a very, very long time. Hopefully I can mitigate this by having it run in the background as much as possible. Either way, we’ll see how far it gets by next week.
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Glad you caught this sooner rather than later. Your attention to detail saved you, even if it meant more work. Little nuances like these are tricky but rather rewarding, especially in fields like these where you can imagine/hear the difference in the two versions.