Automated Speech Recognition (ASR), also known as speech-to-text (STT), is a versatile subfield of computational linguistics that configures technologies that enable computers to recognize and convert natural spoken language into text. 

A chatbot, short for chatterbot, is an artificial intelligence (AI) application that generates dialogue by mimicking human language based interactions through voice commands, text commands, or both. 

Computational linguistics is the scientific discipline which deals with the computational modelling of natural language (both in written and spoken form). Computational linguistics draws from a variety of different fields, including linguistics, artificial intelligence, cognitive science, and so on, to facilitate human interactions with machines by allowing them to gain a computational understanding of language. 

Conversational AI is a combination of technologies, such as chatbots and voice assistants, that users can communicate with to receive assistance. An effective conversational AI application combines machine learning, natural language processing (NLP), and sometimes even IVR and ASR to achieve the most human-like interaction possible. 

Conversational Process Automation (CPA) uses artificial intelligence to bridge the gap between the customer facing world and process automation systems. CPAs are quite special because they automate both conversations and processes.

Conversational user experience (CUX) is a human-like conversational interaction between people and computers in either text (chatbot) or voice form. CUX is aimed at providing users with a more personalized interaction by lessening the robotic feeling computers tend to emit. CUX does this by understanding a user’s intent by using artificial intelligence models such as natural language processing.

Released in mid 2020, GPT-3, or Generative Pretrained Transformer 3, is OpenAI’s third generation language prediction model within their GPT-n series. The tool uses pre-trained algorithms and deep learning in order to generate human-like text. GPT-3 algorithms were fed an exuberant amount of data, 570GB to be exact, by using a plethora of OpenAI texts, something called CommonCrawl (a dataset created by crawling the internet). GPT-3’s capacity exceeds that of Microsoft’s Turing NLG ten times over and it’s known to be the largest existing neural network model existing to date. 

Interactive voice response (IVR) systems are automated voice responses interacting with a user. A caller typically engages with an IVR system by listening to a menu and responding by selecting a number on his phone to trigger a series of appropriate systemic responses. 

A knowledge graph (KG) organizes data from various sources, gets information on entities in a specific domain (e.g., people or places), and creates connections between them in order for the data to be made understandable by the computer. The machine then retains this information as knowledge, using it at different times and in a variety of different circumstances.

Machine Learning (ML) is a method stemming from a branch within artificial intelligence that enables machines to make decisions or predictions based on data rather than a predefined algorithm. A widely known example of applied machine learning is Gmail Inbox's Smart Reply system, assisting people by automating 10% of their email responses.It is based on the foundation that systems can automatically learn from sample data sets (known as "training data") to characterize patterns that help create predictions and fashioning decisions with minimal human intervention.

Natural language generation (NLG) is a subsection within Natural Language Processing (NLP), the border domain that encompasses all software in charge of interpreting and generating human language. 

Natural language processing (NLP) is a branch of technology that handles the interactions between natural human languages and machines. Natural language processing uses a combination of computational linguistics, machine learning, and deep learning models to train machines to understand speech and respond in much the same way as human beings would. In other words, the system can process and fully understand the input language (whether it be in text or voice format) and respond in a meaningful way by comprehending the writer’s intent and sentiment. 

Natural Language Understanding (NLU) is a branch of Natural Language Processing (NLP) that enables computers to understand the meaning of texts. In other words, it’s the process of transforming human language into a format understandable by machines. Once the meaning of a text is understood, computers can interact more naturally with its users, boosting the overall experience.

Robotic Process Automation (RPA), also known as software robotics, refers to a technology that automates repetitive, rule-based digital tasks such as re-entering data, copying, pasting, etc. Traditionally, another form of process automation was more commonly used, namely, business process automations (BPAs). This software is geared to automate routine business tasks and requires a software developer to produce a list of actions into the back-end system in order to automate a specific task. 

Voice Assistants (VA) are a combination of technologies that include natural language processing (NLP), voice recognition, and voice synthesis to communicate with its users using natural language. Voice assistants are commonly confused with virtual assistants, an umbrella term encompassing various types of agents that perform different tasks and individual services. Although virtual assistants can perform similar tasks, they are not entirely synonymous with one another.