What is a voice bot?
A voice bot is a conversational solution that uses artificial intelligence (AI) and natural language understanding (NLU) to help interpret intent and meaning in speech commands. This technology, also known as conversational interactive voice response (IVR), enables users to interact with a device simply by speaking. As voice is one of the quickest forms of human communication, voice bots offer a secondary level of customer service by presenting another way to reflect your brand.
And it’s not just about understanding words. Voice bots determine what the customer wants and guide them to an efficient response. Constantly improving itself and the customer’s experience, voice bots make it possible to achieve multiple tasks simultaneously and successfully.
How do voice bots work?
Voice bots understand natural language and can initiate or participate in a two-way communication with users. With user commands, voice bots can use modules to listen, understand, and learn throughout their usage.
A voice bot uses the following programs and processes when interacting with a user:
- Speech to Text. Input voice recognition and translation, known as speech-to-text (STT), converts natural speech to text by recognizing different accents and languages.
- Text to Speech. With a text-to-speech (TTS) engine, a voice bot brings text to life by translating it into synthesized speech.
- NLU engine. This helps bots understand questions, words, and sentences so the user can speak freely and respond instantly with more than just “yes” and “no” responses.
- Natural language generation (NLG). Answers will be translated into language that the user will understand.
- Language detection. The user’s language and dialect will be recognized and the voice bot will seamlessly switch to that language.
- Machine learning. The voice bot automatically self-learns from the user’s questions and data and adds these learning to the voice bot’s knowledge base.
The benefits of a voice bot
Your business can greatly benefit by adding a voice bot to your business processes. With voice bot AI, your business would be able to:
- Provide a smoother, more accessible customer service experience with round-the-clock availability.
- Recognize current customers and provide relevant history, preferences, and data for personalized interactions.
- Provide seamless interactions between voice bots and human agents to support omnichannel customer journeys.
- Scale and meet customer support needs effectively without adding majorly costly additions.
- Improve employee satisfaction rates by reducing team workloads and stress levels to work on more complex customer service plans.
Where to deploy a voice bot?
As with other bots, such as chatbots, voice bots are best suited for specific channels and instances where it makes sense for customers to interact using their voice. Some of these channels include:
- Internet of Things (IoT) devices. Deploying a voice bot through these devices can make it easier to control the IoT devices themselves, such as smart lights or thermostats.
- Virtual assistant devices. While devices such as Siri and Amazon Alexa are actually voice bots themselves, these devices also support voice bot deployments that enable a myriad of capabilities for the device itself or IoT devices they’re connected to.
- Telephony. Perhaps the largest-growing channel, telephony enables you to call voice bots on a phone line in your chosen language. This deployment typically supports a company’s customer service effort to help save time, costs, and resources.
A big part of why some voice bots work so well is that they’re part of the multimodality capabilities of conversational AI.
What is conversational AI?
Conversational AI is a set of technologies behind automated messaging and speech-enabled applications offering human-like interactions. Combining both art and science, as well as processes language detection and machine learning, conversational AI recognizes speech and text, understands intent, and deciphers languages so it can respond accordingly.
Incorporating context, personalization, and relevance helps make these conversations sound human and more natural. Conversational design, a discipline dedicated to designing flows that sound natural, is a vital part of designing conversational AI applications.
ASR and NLU work together here at the start of the process—ASR listens to what your user wants to do while NLU understands the question and possible avenues of answering that question. Both of these processes, ASR and NLU, help your conversational bot form a proper response while NLG puts that response in language that the user can understand. Throughout, machine learning automatically studies these queries to create future algorithms that learn from the data, identify patterns, and make the decisions needed to form the correct answers for every user in the future.
Chatbots vs. voice bots
As your business starts to see the value of adding automated services into organization-wide programs, decision-makers still need to choose which would work best: chatbots or voice bots. And while the terms are sometimes used interchangeably, chatbots and voice bots are very different in the way each tackle the same task.
Like voice bots, a chatbot is an automated conversational interface. Chatbots are a type of software that communicates through a conversational interface. There are two types of conversational chatbots: rule-based and AI. Rule-based chatbots are decision-tree bots trained to understand questions based on contextual expressions, while AI chatbots are built to learn and improve over time. In simpler terms, voice bots are chatbots with a voice.
When deciding between using chatbots and voice bots, there are five things to consider:
1. What’s your niche?
If you’re in an industry where users need to provide a lot of sensitive information before speaking with a human agent, they may or may not feel comfortable doing so.
2. Who are your customers, and how do they communicate with you?
Are your users tech-savvy or do they need a bit of help? Are they quicker to call your customer service technicians or exhaust social channels and email your team before they decide to speak with a representative? Understanding what your users prefer will determine which option would work best for them and, ultimately, your business.
3. How do you deliver information?
You deliver information to users in three ways:
Large amounts of information are most easily processed quickly by seeing, followed by hearing. To deliver a lot of information at once, a voice bot is a better choice for your task, but depending on your customers, reading short phrases from a text-based chatbot might be a better option.
4. How complicated is your process?
Pinpoint which are your most complex customer inquiries and how long will that take to solve. Decide if a bot can work in the background, helping your process move faster. Or, if the quickest route is jumping between multiple support teams, then using a chatbot would be easier.
5. What types of information are you processing?
Images, text, and audio are all possibilities—learning and understanding which types of information you’ll be processing every day is critical in choosing which type of bot you’ll need.
Voice bots and chatbots have their own sets of advantages and disadvantages. In fact, your business may even be able to use both. By deciding on the needs of your users and which communication channels they prefer, you’ll be able to determine which will work best.
There are many products and solutions available to help you engage with customers on a new level by providing informative and robust customer service. One such offering, Microsoft Power Virtual Agents, will help you build, test, and publish bots easily to handle a multitude of tasks and answer complex questions quickly—all while easily integrating them into your existing systems.