VOICE BOTS Voice bots are software powered by artificial intelligence (AI) that allows a caller to navigate an interactive voice response (IVR) system with their voice, generally using natural language. Advantages 1. Natural way of communication 2. Suits larger customer bases: Being a natural interaction method, voice makes it easy for people of all ages to engage with interfaces, in a limit-free environment. 3. Smoother UX: Voice bots are simple and natural alternatives to conventional DTMF IVRs. 4. Multi-tasking customer service tools. Because the commands are voice-based alone, customers can engage in customer service interactions even while going about their everyday routine – say driving or cooking. Working Principle The building blocks required to build a robust, AI-powered voicebot include: • Automatic Speech Recognition — Listen • Natural Language Understanding — Understand • Conversations Module — Determine • Text-to-Speech System — Speak Automatic Speech Recognition Technology Speech recognition models use advanced algorithms to capture data from a caller’s voice, filter out background noise, and learn voice patterns in real-time. VOICE BOTS Natural Language Understanding A layer of NLU is included while building a voice bot to achieve a higher level of understanding. An NLU engine enables a voice bot to understand the intent behind the customer’s speech and identify and extract entities from it that drive the conversation turns. For example, a travel bot identifies the below intent: When a caller says, “Please book me a flight for next week,” the NLU engine helps the bot to identify that the intent behind the caller’s request is BookFlight. However, humans do not always express themselves in a specific way. The NLU layer enables the bot to understand and connect various requests to a particular intent. Like when the caller says, “I need to fly to London,” the NLU accurately comprehends the user intent here as BookFlight too. Conversations Module Contextual conversation makes interaction with a bot a humanized experience. It lets users interact naturally and does not force them through a specific flow. The conversational approach focuses on the user request context, identifies the intent, and gathers all the related information through fully autonomous natural, unstructured dialogues. For example, when the caller says, “I need to fly to London,” the voice bot understands the context, identifies the intent as BookFlight, and requests the caller for the missing information. Text-to-Speech Text-to-Speech turns text into natural-sounding speech. It is a computer-generated simulation of human speech using deep learning methods. Important Use Cases 1. Conversational IVR 2. Identification and verification: Almost every contact center interaction starts with agents asking the callers to identify themselves by providing specific information — phone number, date of birth, order id, PNR, etc. This takes up a lot of live agents’ time, adding to the cost and forcing agents to rush through the actual resolution. Voice bots automate the identification and verification process by collecting relevant information and passing it to the agent before they get connected. 3. Autonomous customer support ensuring Zero wait time 4. Outbound calling: Voice bots can proactively call customers for notifications like reminders, due dates, offers/discounts, and renewals. It has a wide range of use cases across industries that save businesses both time and money. VOICE BOTS
