Systems like Alexa and Siri have created a new field of research in cognitive science that examines the effects of conversational devices interacting with humans. With the onset of the pandemic, touchless technologies like voice-activated assistants and applications have helped to reduce and eliminate touchpoints and increase safety. With the growing use of smartphones, voice technology has also been growing rapidly. Voice interfaces are advancing exponentially in all industries, with significant advancements in healthcare and banking. Several companies are launching their own voice technologies to satisfy the market demands. In this article, we have listed the top 10 key predictions for voice technology in 2022.
Voice notifications are valuable tools that enable users to engage more with their devices. Notifications are helpful for reminders, promotions, and information. Push notifications can help businesses have a stronger chance of reaching their audiences. Voice assistants are designed to connect the third-party apps for voice push notifications.
As voice technology grows, business leaders are deploying a string of new applications, which is leading to an increasing number of consumers turning to voice engagement. Voice-enabled chatbots provide several benefits like faster responses and zero time wait, better two-way interactions, enhanced customer experiences, and fraud detection, to name a few.
The advanced interactive voice response (IVR) and a call tracking system can significantly improve sales and customer satisfaction. Businesses can use intelligent virtual agents powered by NLP engines to answer customer queries in real-time or create outbound calls with the click of a button. Implementing a smart call tracking system in a business IVR can create robust data that can be used to generate sales for outbound processes.
Online search trends show that users are increasingly searching for local results. Consumers are using more voice technology to search for local restaurants, establishments, or locations. For local searches, voice assistants can suggest from the local SEO-optimized voice search entries. They only provide citations from trusted sources, which is how voice search works.
Experts believe that the number of individuals using smart speakers will further grow in the future with the implementation of 5G networks. Currently, the most common use of a smart speaker involves playing music, weather forecast, and general online search. Researchers predict that smart speakers can be used for more serious activities like managing finances, booking hotels and flights, and other activities.
Voice cloning is a process that uses machine learning along with neural networks to generate realistic human language text-to-speech platforms to mimic how the brain processes human language and exhibit outstanding efficiency in the learning patterns of data. With the help of AI, neural networks, and cloud-based GPUs, start-ups can create a computerized voice and make it indistinguishable from the voice of a natural person.
Advancements in AI and ML have made a huge impact on how we interact with our smart devices and search over the internet. Google RankBrain is a prime example that is designed to recognize phrases and words to learn the instructions and yield almost appropriate results. The increasing use of AI-powered devices means search algorithms must evolve not only to accommodate machine learning but also to support the growing use cases in voice technology.
The importance of text-to-speech and voice recognition cannot be ignored in creating a more immersive gaming experience. It is not an easy task, considering the vast possibilities of the different types of voices. But generative neural networks are machine learning tools that are making this possible.
The global movement to perfect voice technology means marketers will have to regularly innovate their SEO strategy to optimize voice search. Businesses seeking to attract the most possible inbound traffic must implement Voice SEO to move forward.
Personalization is crucial to building meaningful relationships with customers. Businesses can use ML and NLP along with sentiment analysis to identify the true meaning of customer requests and queries. By identifying those intents and purposes, brands can generate accurate responses for customers.
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