But how does the listener break down information when both a man and a woman are saying the exact same thing? According to research, the voice itself is the source of unconscious bias for the listener, and women are interpreted differently as a result.

Meghan Sumner, an associate professor of linguistics at Stanford University, stumbled into the unconscious bias realm after years of investigating how listeners extract information from voices, and how the pieces of information are stored in our memory. Study after study, she found that we all listen differently based on where we’re from and our feelings toward different accents. It’s not a conscious choice, but the result of social biases that form unconscious stereotyping which then influences that way we listen.

“It’s not always what someone said, it’s also how they said it,” Sumner tells Fast Company. “How we view people socially from their voice, influences how we attend to them, how we listen to them.”

For instance, in one experiment, Sumner found that the “average American listener” preferred a “Southern Standard British English” voice rather than one who had a New York City accent, even if both voices are saying the same words. Consequently, the listener will remember more of what the English speaker says and will deem them as smarter. All of this is impacted by the stereotypes that we have of British people and New Yorkers.

Even if you don’t have any association or interactions with a group of people, a listener can still presume they know what those people would say. For example, if you don’t interact with women often, you might still assume you know what women talk about. It doesn’t matter what the woman is actually saying because the listener will always automatically anticipate what she’ll say next, or what she’s trying to say.

Often, this stops us from truly listening to what people say. In another small study, Sumner and her colleague, Ed King, found that if a man says the word “academy,” the listener might assume that he’s speaking about a school, but when a woman says “academy,” listeners will more likely presume that she’s talking about an award show.