We’ve all heard that first impressions are important, but they run deeper than your snappy outfit and the firmness of your handshake. Thanks to new research published in the March 2018 edition of the journal of the Proceedings of the National Academy of Sciences, we now know the way you say hello to another person is also part of the package.
Whether we realize it or not, we already have an ingrained idea of what a proper hello should sound like — the same way we can all mentally picture what an apple looks like (shiny, red or green with a stem). We judge people by the way they greet us, deeming them to be friendly or hostile; trustworthy or dishonest.
Most of this comes down to intonation, the study reveals. “We form mental representations of others’ personalities according to the acoustic qualities of their voices,” a statement on the study reads. Researchers created software that takes a recording of a single word — like “hello” — and generates thousands of different ways of saying it. They then had study participants react to each different variety of the greeting in order to determine which were deemed “sincere.”
The results were interesting and pretty specific. For instance, in order to sound determined, a French speaker must pronounce “bonjour” (French for hello) with a descending pitch, putting emphasis on the second syllable. On the other hand, if a French speaker wants to sound trustworthy, they should ensure that the pitch rises quickly at the end of the word. The findings were the same, regardless of the gender of the person speaking.
So, aside being able to help control how people perceive you, what other benefits are there to this research? The people behind the software hope it may help understand how emotions are represented by people on the autism spectrum and have made the software freely available to them. In addition, the researchers also aim to use the software to study how words are interpreted by survivors of a stroke (which can alter how the person perceives vocal intonation). Lastly, “whether for the purposes of medical monitoring or diagnosis, the researchers would like to use their method to detect anomalies in language perception and possibly make it a tool for patient rehabilitation,” the statement read.
Medical software that advances how we understand autism and strokes and lets us make snap judgments about people based on one word? This study had me at hello.