How does conversational AI work?
How does conversational AI work?
Using technology such as natural language generation, machine learning, and natural language understanding, conversational AI can provide exceptional text-based or voice assistance.
Need an example? Let’s look at the steps that an AI chatbot takes to leverage conversational AI that’s been trained with company-specific keywords:
- Input generation—the customer either says or types their request.
- Automatic speech recognition (ASR)– allows the AI to break down the sounds it receives through your phone speaker and arrange them into words. The simplest version of ASR requires specific words to be spoken, while higher-level technology can accept normal human speech patterns, including slang and mispronunciation.
- Input analysis—natural language processing (NLP) cleans up the request so the artificial intelligence engine can understand it better. Natural language understanding (NLU) may be applied to enable the artificial intelligence engine to comprehend more nuances behind the request.
- Natural language generation—the AI engine formulates a human-like response and sends it back to the customer.
To fully understand these steps, you’ll need to familiarize yourself with some terms used in AI development, such as:
Machine learning.
Machine learning is a key component of artificial intelligence. It means that the system can learn and improve itself over time, without a human needing to input additional information.
This process is based on pattern recognition. The AI engine uses neural networks to spot patterns in data and then provide outputs.
When setting up your customer service software, we help our clients identify and input keywords that are specific to their products, brand, and customers. The AI features then use that foundation to build upon. Over time, Talkdesk developers and data scientists review and will correct these outputs if they are off course. Then, the AI engine will gradually produce more and more accurate outcomes.
The initial human input—and later the correction—is what we refer to as training the AI.
This used to be a difficult, time-consuming, and expensive process. As AI has advanced, innovators at Talkdesk have created a way for the AI to learn on the job through our AI Trainer.
It uses human-in-the-loop (HITL) technology, which lets agents and supervisors engage directly with AI machine learning. It’s code-free and can be done in a few clicks. Sometimes, the agent simply needs to follow some on-screen prompts to help train the AI.
As a result, your AI tools stay highly accurate and fine-tuned to the changes that happen in your business, without the need to bring in AI data specialists for updates.
Natural language processing (NLP).
Natural language processing enables AI engines to pull words from a text or voice-based conversation and interpret meaning. It uses the literal meanings of each word, along with context-driven insights.
For example, the word “free” could refer to something that is received at no cost (i.e. is the product demo free?), or it could mean that someone is available during a certain time (i.e. I am free on Tuesday at 10 a.m.).
NLP empowers conversational AI to tell the difference between these two situations.
Natural language understanding (NLU).
Natural language understanding is a subset of natural language processing. While NLP can categorize what the customer is talking about in a general sense, NLU goes deeper.
It can understand the sentiment, deep context, semantics, and intent of the request.
As an example, say a caller tells a Talkdesk virtual agent that they’re calling in to claim a free product. NLP would allow the AI to understand that by “free”, the caller means “no cost”. NLU would kick in to scan the system for any free product offers that are relevant to the customer on the phone, walking the user through the steps needed to claim their product.
Talkdesk’s integrated AI might also direct that caller to a live agent, automatically providing the information they need to present a relevant offer. And it happens right in the agent’s Workspace application.
NLU is built to overcome obstacles such as mispronunciation, sub-optimal word order, slang, and other natural parts of human speech. As NLU systems advance, they’re even beginning to understand nuances like sarcasm to reduce the possibility of misinterpretation.
Automatic speech recognition.
Conversational AI doesn’t actually pick up on full words. These are too complex to handle, especially over the phone, when you may be dealing with static, background noise, or other interference.
So how does it come up with an appropriate response to normal speech?
The AI breaks down the soundwaves it receives into phonemes—small, distinct sounds that differentiate one word from another. English has 44, including, for example, the “p”, “b”, and “th” sounds.
Automatic speech recognition is what allows conversational AI to distinguish between “pat,” “bat,” and “that” with impressive accuracy.