The Conversational AI and Chatbots Glossary

the conversational ai and chatbots glossary

With the help of the industry’s biggest experts, and as a part of our mission to promote collaboration and create a common ground – we’re launching a professional, yet simplified, glossary of conversational AI terms, concepts and ideas.

All of the explanations are coming from Miri Blyackher’s web series, Coming to Terms with AI, which is featured bi-weekly on CoCoHub’s platforms, including our growing YouTube channel. We’re updating this glossary after each and every episode.

So… let’s start touring our conversational AI glossary! What is…

CHATBOT and DIGITAL ASSISTANT | CONVERSATIONAL AI | NLP, NLU AND NLG (Natural Language Processing, Understanding, Generation) | TURING TEST | ANTHROPOMORPHISATION

WHAT IS A CHATBOT? WHAT IS A DIGITAL ASSISTANT? | THE CONVERSATIONAL AI GLOSSARY’S EXPLANATION

Brielle Nickoloff, Linguist, Conversational AI Advocate and Product manager in Botmock:

A digital assistant is any kind of conversational experience that helps you achieve something. It can be a transaction where you’re buying something, it can be informational, where you’re learning about something. It can be organizational if it’s helping you keep track of something on your calendar. 
Under the umbrella of the digital assistant you have chatbots and voice bots. So, talking with a voice experience like Alexa or Google assistant or Third-party application, you’ll be mainly using your voice and keeping in mind – as the designer – that they can’t see anything, unless you’re using a screen device. 
If you’re using a chatbot, its natively existing within a screen like a mobile phone or on your desktop. So you have the luxury of allowing the user to see that information for a longer period of time. It doesn’t just disappear Into thin air as soon as it’s said. 

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WHAT IS CONVERSATIONAL AI?

Rucha Gokhale, Founder of Indyrise and co-founder of Women in Voice NJ, explains to the conversational AI glossary:

Conversational AI is bringing the ability for you to talk to the computer in your language, instead of the need for you to learn the computer’s language.

A human-to-human conversation is very difficult to replicate with a computer, because of things like body language, changing directions, nuance. In other words, the computer will essentially do what we tell it to do. And we really haven’t really codified conversation deeply enough for a machine to do it well. 

If you’re going to have a machine have a conversation at the lower level with humans, there are components like intents, entities, slots or data – that helps codify conversations so that we can implement them in an AI platform. 

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WHAT IS NLP/NLU/NLG – NATURAL LANGUAGE PROCESSING. NATURAL LANGUAGE UNDERSTANDING, AND NATURAL LANGUAGE GENERATION? | THE CONVERSATIONAL AI GLOSSARY’S EXPLANATION

Dr Joan Palmiter Bajorek, Women in Voice CEO & founder:

Natural language processing, NLP, is literally how computers process human language. Natural language is kind of a misnomer, but it really means human language. For example, take the sentence “the cat lies on the table”. And so the computer is like “the cat”, “lies” “on the table”. So, we’re thinking about “the cat” or about different parts of the words, like “cat”, which is a noun. Traditionally natural language processing is on the word level and syntax. So – word and the order traditionally, that’s what it’s all about.

Natural language understanding, NLU

Natural understanding implies that we have more semantic material. So that the word “cat” means something. We have some knowledge behind it instead of it just being three letters referring to a noun. Suddenly “cat” and “lies in the table”, there’s some context around it. There’s some understanding that we couldn’t switch things around – “the table lies on the cat”. Understanding is part of it, and a lot of people “know” and “understand” the computer. So it’s not just the words, but also understanding them. It’s also figuring out the meaning behind the words.

Natural language generation, NLG, is the output. Like, when you’re doing texting and it guesses the end of the sentence – we are generating by probability. We see all these other words, we think we might know what the next word is. It sees the other words and it’s trying to guess what the next word is.

Usually on the back end we have multiple options, ranked by percent: 80% chance it’s this, 2% chance it’s this. So, it’s trying to guess based on lots of things, but that’s what NLG is about, or creating the words, the language, the next sentence. As a result, it’s probably not going to be creating something new. It has a dataset behind it that it’s looking at to consider the future. Most importantly, that’s why a lot of people want big a dataset on the backend to consider what the future could look like.

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WHAT IS The Turing Test? | THE CONVERSATIONAL AI GLOSSARY explanation

Galit Galperin, product executive and author of the popular blog Voicey.co.il:

The Turing test is a term named after the British scientist Alan Turing. Back then in 1950, he wanted to check in if computers can talk like a human, and imitate human intelligence. Turing based his test on the imitation game – a party game in which a man pretended to be a woman and a judge tried who was who, by asking the concealed player questions.

In the Turing test, the judge would try to guess who was a computer and who was a real human. So, all the participants would be separated from each other. The judges in the tests know that some of the testers are not human and they try to identify them. Therefore, if the evaluator could not reliably tell the human from the AI, the AI would pass the test.

The test does not check the ability to give correct answers to questions; But to see only how closely the answer resembles to those a human would give. In other words, a computer would be considered intelligent if its conversation couldn’t be easily distinguished from a human’s. So, a computer that’s mistaken for a human more than 30% of the time during a 5-minute keyboard conversation, is passing the Turing test successfully.

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WHAT IS Anthropomorphisation? | THE CONVERSATIONAL AI GLOSSARY explanation

Margareth Jabczynski, conversation designer, singer-songwriter and comedian:

Anthropomorphisation is the projection of human traits on objects or things that aren’t human – in this case, chatbots. So, we try to implement a wide range of emotions on a chatbot, design it an inclusive and empathetic way, in order to make it as human-like as it can be. That is the reason we get frustrated when something is “brakes” while we talk to a bot – and the bot is “revealed” as not human.

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