“There’s this interesting disconnect between how helpless a human newborn looks and how sophisticated a baby really is, at least when it comes to listening to language.”
By Michelle Johnson (2/22/19)
Have you always wanted to be a scientist since you were younger?
I have always wanted to be a linguist. I’m Hungarian, and Hungarian is a really weird language, it’s very different from Indo-European languages, and so when I started learning English in school, it was like, “Oh, this is really different.” I think that’s what started [my interest].
What questions are on your mind right now?
I’m looking at how really young babies start learning their native language. There’s this interesting disconnect between how helpless a human newborn looks and how sophisticated a baby really is, at least when it comes to listening to language. It looks like babies are very underdeveloped in many things, but language is something that they’re actually very good at. At the same time, language is a very complicated system. Babies figure it out before they know anything about the world—they will not know many things, but they figure language out. That’s really interesting.
What has it been like working in an interdisciplinary area?
I come from theoretical linguistics, not at all an experimental domain, and so I learned experimental psychology, developmental psychology, neuroscience as I went along. I think there are challenges, namely, often people don’t speak the same language. So, for example, when I say “grammar,” I mean something and they mean something completely different. The hardest thing isn’t to understanding each other once you know you speak different languages, but it’s to realize that when I say something and you say the same, we don’t mean the same thing. Once you’re aware of that, it becomes obvious that you need to solve this in a better way.
What surprised you about working in the experimental domain?
When I started working with babies, which was when I first started working with experiments in general, the first thing I learned was what are called “looking time” measures. Essentially, you present sounds to babies that you’re interested in, but each sound is accompanied by something the baby could look at, like a blinking light. You measure the time the baby spends looking at the light or the visual stimulus and then you infer that that time is the measure of their interest in the sound. When you first run experiments like this, you look at the you video recording of the babies [doing these measures], and you think, “I could never make any sense of this at all—if anybody says that this means anything, then they’re lying. It’s totally unscientific.” Then you learn what you have to look for and it’s starts making a lot more sense, but in the beginning you think, “This is really curious, this doesn’t look like science.”
What’s the best piece of advice you’ve ever received?
It wasn’t an advice, I think it was encouragement. I had mentors who unquestionably trusted me and were giving me opportunities. In retrospect, now that I’m supervising students, you see how hard it is to do. You have to find the right kind of input and encouragement for everybody because saying that something is great may be really encouraging to one person, but to another, it looks like, “Oh, you’re not giving me feedback. She just needs to get rid of me.” It’s really challenging to understand what’s the best; you don’t want to push, but at the same time, you don’t want to look indifferent either. I think the best thing for me was to work with people who were a good match for me.
To learn more about Dr. Gervain and her work, click here