Our language is constantly changing. But what happens when our computers are stuck in the past?
as artificial as the name may imply — it’s largely based on the human brain.Millions of neurons run up and down the nervous system, through the flow of the spinal cord and nooks and crannies of the brain. These neurons move messages between locations, and they meet at synapses. Synapses transfer the messages between neurons by stimulating target neurons, the next step on a message’s journey.
It’s all remarkably human — too human even, because just like humans, NLP often falls victim to bias.In humans, auditory bias can come in many forms. For example, confirmation bias occurs when we only hear what weto hear, picking out details that validate what falls in line with our beliefs. Anchoring bias occurs when the first piece of information we hear changes how we perceive the rest of the information, like in bargaining when the starting price sets the stage for the rest of the deal.
The study went a step further. It investigated the impact of gender on the word error rate. While the algorithm incorrectly identified the men’s speech roughly 40% of the time, it incorrectly identified more than 50% of the women’s speech. Depending on the accent, discrepancies between female and male speech could be as high as 30%.
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