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Voice AI – A Cutting Edge Voice Technology From Conversational AI Space

Conversational AI, Conversational UI, Conversational User Interface, Chatbot, Customer Service, Digital Transformation, Virtual Customer Assisstant (VCA), Intelligent Process Automation (IPA)

Artificial Intelligence (AI) is ruling various industries for a long time now, to add on to that automation has also come a long way in changing the customer interactions and providing technologies which will help them to improve customer services across the enterprises.

What is Voice AI?

The term Voice AI is associated with Conversational AI which gives human-like voice commands to customers. Voice AI is a conversational AI tool that receives and interprets commands using voice commands. Devices can interact and respond to human questions in natural language using this technology.

The voice AI chatbot has given businesses a great opportunity to serve customers by being able to understand and communicate in human language. It aids in the acceleration of processes, the increase of productivity, and the scaling of operations.

Voice AI has been very popular among customer service processes which provides an ability to recognize and respond to customers in human language. with its quick resolutions, high agent productivity, and scale in customer support, Voice AI has been helping businesses more often.

Why are Businesses Implementing Voice AI?

The answer is simple, Voice AI is providing customer demands as per their request. These Voice AI assistants such as Siri, Alexa, Google Assistant, Amazon Echo, Google Home, and so many others are answering queries of users within a few seconds. The ecommerce space is now getting acquainted and more dominated by these Voice AI assistants.

Voice AI Operates Conversational AI Space

Voice AI is slowly driving the conversational AI space and getting more attraction from businesses that provides automated basic, mundane tasks, answer queries from users, and so on. Conversational AI delivers flexible customer service without any human intervention, it is an integrated platform that has the ability to recover customer data and account details in no matter of time which leads to proper transactions and workout of customer queries. Businesses now noticing the facts about conversational AI and taking advantage of these benefits.

So far, conversational AI was applied to the chat interface, but now undeviating Voice AI has also made a positive impact on businesses.

Another advantage voice Al has over chat Al is that it’s inclusive of a wider demographic. For older adults and non-familiar tech users, this technology helps them to engage with It and find more answers to their queries. Voice AI has made its mark with its multiple applications in the customer service area. It has helped inbound use cases like answering simple customer queries and arranging appointments to making reminders and updates to customers which are outbound use cases.

The average resolution time and average ticket handling time are both significantly reduced when using Voice Al. When compared to phone support, customers must spend significantly less time getting answers to their questions.

How does AI’s Voice work?

Automated speech recognition (ASR), natural language processing (NLP), and natural language understanding (NLU) have made it easier to understand human speech, interpret it, and respond to users with accurate answers in the last decade.

  • Acknowledging human speech: Understanding what the user is saying is the first step. The sound waves are converted into text for this. The speech recognition algorithm further breaks down the sentences into smaller word-groups/sentences that the machine can understand.
  • Getting rid of background noise: Background noise is something that inevitably creeps into speech. When a user speaks into a microphone, a lot of background noise is picked up. To correctly interpret a customer’s intent, it’s critical to filter out irrelevant words and separate the message from noise.
  • Neural networks are a class of algorithms that are used to understand the relationship between data points. The input data is further decomposed into smaller bits, which are analyzed and matched with the best and most relevant option.
  • Using syntactic and semantic techniques: This works in tandem with neural networks, where the Al recognizes grammatical nuances in the input data. That many people can’t speak grammatically correct English, and sentence structure is easily misunderstood. Semantic analysis techniques delve deeper into words and sentences to discover the true meanings.
  • Reviewing feedback: After carefully analyzing the input, the Al arrives at a few potential solutions and selects the response that best matches the query.
  • Replying to the user: The final step is to present the final choice to the user. The response is converted to an audiobook and delivered to the users via text-to-speech technology.
Challenges in Voice Al Standard Procedure

No technology comes without its set of challenges. For one, it’s not easy to develop an Al that’s good at understanding user intent and responding with an accurate response and a high precision rate. Some of the challenges are whether AI can process words when anyone is speaking fast, can it decode various accents and dialects, and also can AI recognize slang that is more likely to be found in normal speech than in any text?

Other than Al, there are obstacles to overcome. Users are more aware of their data these days. The first question they ask when they use new technology is whether it is safe to use. When companies ask users to adopt this technology, they must address this issue.

Voice Al can Lead Customer Service Space

To connect with users, the Voice Al platform provides delightful experiences and a simple and familiar interface. Voice call automation has a direct impact on call center volumes and agent workload.

Businesses and users can connect with the system more effectively with the help of the Voice AI platform. The voice AI call center is the most compelling advancement in voice recognition technology because it relieves the burden on customer service representatives.

It also provides an additional layer of security by analyzing patterns to authenticate a speaker’s voice. This is especially helpful in the banking and e-commerce industries when it comes to preventing fraud.


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