In today’s digital marketplace, conversational AI has become a powerful tool, transforming how businesses interact with the outside world, streamline services and create engaging, customer-focused experiences. You can see my previous post on these exciting developments, as well as some of the most common use cases, here.
But have you ever wondered exactly what happens behind the scenes?
Everything You Need to Know About Conversational AI
In this post, I’ll outline the key technologies, techniques and methodologies that bridge voice communications and conversational AI, making the concepts easy to understand for everyone. After all, voice is the most intuitive and preferred way for most people to communicate.
Whether you’re a seasoned tech enthusiast or new to the field, I’ll explain how these innovative solutions enable AI to understand, process and respond to voice commands in a natural way, just like a human would. Let’s get started.
Speech-to-Text (STT)
Speech-to-Text allows users to convert their spoken words into written text. Text is a fundamental medium through which computers can interpret and process human language.
Text-to-Speech (TTS)
Text-to-Speech converts written text into spoken words, using speech synthesis techniques to enable machines to communicate with humans in a natural-sounding voice.
Natural Language Processing (NLP)
Natural language processing enables computers to analyze, understand and generate human language in a way that is meaningful and useful for various applications. NLP analyzes large amounts of natural language data to comprehend how humans communicate. It includes the following sub-categories:
- Natural Language Understanding (NLU): Natural language understanding is a subset of NLP that focuses specifically on understanding the intended meaning of language to ensure that the machine accurately understands what is being communicated.
- Intent Recognition: Intent recognition is a component of NLP that aims to understand the intention behind a user's query or command by analyzing the spoken language to grasp the user's intent, making interactions with AI more intuitive and efficient.
- Named-Entity Recognition (NER): Named-entity recognition is a crucial component of voice applications that assists in extracting and categorizing key information from spoken language, such as names, dates and locations.
- Large Language Models (LLM): Large language models can understand and generate human language by processing vast amounts of text data. LLMs are a foundational component of conversational AI for interpreting context, understanding intent and generating human-like responses.
- Small Language Models (SLM): While LLMs are models trained to solve many types of complex tasks and require large computational resources to run, small language models are built to solve specific tasks and trained on smaller amounts of data. They are generally easier to train, fine-tune and deploy, and are also cheaper to run.
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Affective Computing
Affective computing can recognize, interpret and process human emotions. It uses voice analysis to detect and respond to the emotional state of a user, enabling machines to interact in a more human-like and empathetic manner.
Voice Recognition
Voice recognition encompasses the entire process of understanding spoken language and includes technologies like STT and TTS.
Machine Learning Algorithms
Machine learning improves conversational AI by refining algorithms to deliver more human-like and effective conversations.
Generative AI
Generative AI refers to AI techniques that learn a representation of artifacts from data and use them to generate completely original artifacts that retain a likeness to the original data, such as text, images, video and audio. In terms of conversational AI, the technology enables systems to respond to questions accurately and in a human-like fashion.
Bring Conversational AI to Life with AudioCodes
If you’re keen to get started with voice-enabled conversational AI in your organization, AudioCodes offers a straightforward way to take the leap.
Get in touch with us to start your AI journey today.
