Voice AI is a conversational AI tool that uses voice commands to receive and interpret directives. In this post, we answer how does voice recognition work.
The terms automation and artificial intelligence (AI) have changed the way businesses interact with users globally. By offering a seamless experience that allows the users to connect with the technology and get a range of services, voice AI is a new addition to the list of the fast-growing technologies.
In this article, we cover:
- What is voice AI?
- The basic working of voice AI
- Roadblocks in working of voice AI
- Voice AI: The future of customer support
What is voice AI?
Voice AI is a conversational AI tool that uses voice commands to receive and interpret directives. With this technology, devices can interact and respond to human questions in natural language.
With the ability to understand the human language and communicate with them, the voice AI chatbot has offered a great opportunity to businesses to serve customers. It helps speed up processes, increase productivity and scale operations.
According to the Pew Research Center, approximately 55% of virtual assistant users prefer speech recognition apps as they offer hands-free operation of devices. With the current trend, the voice-based speaker market could be worth $30 billion by the year 2024.
The voice AI assistants, namely Amazon Echo, Siri, Google Assistant, Google Home, Amazon Alexa, and others are a few incredible advances that have replaced the need for touchscreen devices. Experts expect voice-based shopping will reach $40 billion in 2022.
With the increasing use of the voice AI platform, one is curious to know how does voice recognition work? Understanding how voice control technology work is essential to know the key factors to tackle while adopting voice AI.
Suggested Reading: 5 Tips on How to Leverage Voicebot to Improve User Experience
The basic working of voice AI
The voice AI is based on understanding the human language and interpreting the same to offer appropriate results. AI programming perfects its algorithms to constantly provide the best rational answer. A mixture of AI and automation helps develop speech systems.
Like when two people communicate, there is encoding and decoding of the message; voice AI works similarly. Below, we discuss the steps involved in speech recognition in AI.
1. Understanding the speech to text
The first step of the process is to understand the speech of the speaker. The sound waves generated by the speaker need to be interpreted and analysed to break them down into fractions of text.
Companies use the pre-speech recognition technique for this step. User’s words are broken down into groups by the AI. In the process, the words are converted into bits that are easily understandable by the system.
Learn how Verloop.io Improved its ASR accuracy with error correction techniques here.
2. Filtering ambient sounds
There are chances that in addition to the words spoken by the user, some ambient sound is picked up by the AI. Say connecting with a call centre while on the road can increase the chances of recording the surrounding disturbances like horns or announcements going on in the message.
Being sensitive to such pitches, the AI can separate the message from noise with the help of a neural network.
3. Transfer to neural processing
The voice AI is based on the neural networks that replicate the neurons in a human brain. The set of data that reaches the system is further broken down to find the best match.
Reading and analysing every single letter of the message, the AI tries to analyze the sentence’s meaning and match it with the best possible outcomes.
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4. Syntactic and semantic techniques
The voice AI is now ready to act. Using syntactic and semantic techniques for analysing text, the AI gets a deeper understanding of the context under consideration.
Here, the syntactic analysis further breaks down the natural language for the grammatical rules. Moreover, semantic analysis is based on understanding the meaning of the sentences and words.
5. Response evaluation
The AI reaches a specific range of conclusions by carefully examining the question of the user. The algorithm further analyses the most potential solution and filters the responses to find the perfect match to the query.
6. Communicating to the user in the language
In the last step, the selected response is communicated to the user. Here the user receives the response to the query while at the same time AI converts the data in audio format. The AI also saves the response for future reference.
Roadblocks in working of voice technology
Now that we know how speech recognition work in artificial intelligence, let’s understand what makes this difficult to implement.
According to Statista, the accuracy rate of the Google Assistant is around 98%, making it the “smartest” voice assistance available. Nevertheless, companies suggest that developing voice-based devices is difficult.
The fundamental roadblocks in the working of the voice AI assistant are:
- The AI picks up ambient noise and the surrounding sounds, creating confusion.
- The technology finds it difficult to understand fast speeches. Usually, more than 200 words per minute are hard to understand and interpret.
- The accent and dialect differ with the region, so it is essential to add the feature to catch the different dialects.
- Understanding the context of the speech is also complex and time-consuming.
Related: How to Measure the Success of Your Voice AI Bot?
Voice AI: The future of customer support
Voicebots use cases include offering excellent support to businesses and users to connect with the system effectively. Reducing the burden on the customer support staff, the voice AI call centre is the most compelling advancement in voice recognition technology.
It also adds an extra layer of security as it can authenticate a speaker’s voice by analysing patterns. This is extremely useful in fraud prevention, especially in the banking and e-commerce sector.
Deloitte’s Beyond Touch: Voice Commerce 2030 study noted that e-commerce will generate 30% of sales via voice commerce by 2030; this undoubtedly emphasises the future trend of the technology, the adoption of voice AI.
Verloop.io’s Voice AI for customer support helps businesses effectively and efficiently communicate with their customers. Brands can delight their customers with voice and text-based chatbots with round the clock availability and multilingual capabilities. Our conversational AI platform is available on the website, in-app, WhatsApp, Facebook and Instagram.