For example, reading a sentence and being able to identify what words act as nouns, pronouns, verbs, adverbs, and so on. Part-of-Speech Taggingįrom a very small age, we have been made accustomed to identifying part of speech tags. The primary use case being highlighted in this example is how important it is to understand the difference in the usage of the word LOVE, in different contexts. This is just an example of how teaching a robot to communicate in a language known to us can make things easier. And maybe when you are telling your partner “Lets make LOVE”, the dog would just stay out of your business ?. He would also realize that it’s an emotion that we are expressing to which he would respond in a certain way. What this could mean is when your future robot dog hears “I love you, Jimmy”, he would know LOVE is a Verb. It is these very intricacies in natural language understanding that we want to teach to a machine. Since we understand the basic difference between the two phrases, our responses are very different.
That is why when we say “I LOVE you, honey” vs when we say “Lets make LOVE, honey” we mean different things. We as humans have developed an understanding of a lot of nuances of the natural language more than any animal on this planet. Instead, his response is simply because he understands the language of emotions and gestures more than words.
This doesn’t mean he knows what we are actually saying. That’s how we usually communicate with our dog at home, right? When we tell him, “We love you, Jimmy,” he responds by wagging his tail. Let’s go back into the times when we had no language to communicate. By Divya Godayal An introduction to part-of-speech tagging and the Hidden Markov Modelīy Sachin Malhotra and Divya Godayal Source:
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