The evolution of voice recognition takes the smart home to the next level

Voice recognition technologies are advancing in IoT devices, promising to transform the connected home. Since its inception in the 1950s, speech recognition has evolved, reaching remarkable accuracy in 2018 and accelerating due to the pandemic. There are expected to be 8 billion digital voice assistants in use by 2023, driving a market of $31.82 billion by 2025. These systems enable smart home automation beyond device management, incorporating emotion-based interaction and context, and opening possibilities for new uses.

Voice recognition technologies mature into a new generation of IoT devices that promise to further revolutionize the connected home.

The first speech recognition systems, developed in the early 1950s, only had the ability to interpret numbers. It was only several decades later, by 2018, that the level of human voice recognition accuracy was perfected, expanding to a variety of industries and connected devices. 

In fact, the pandemic made it all the more necessary to rethink the way users interact with devices, in favor of contactless systems. In addition to mentioning that the customer experience gains in comfort by adding verbal commands.

The estimates They note that there will be 8 billion digital voice assistants in use by 2023, up from an estimated 2.5 billion by the end of 2018; a market that, on the other hand, is expected to reach $ 31.82 billion by 2025.

Industries of all kinds are combining IoT capabilities with speech recognition technology to meet changing user demands, process enhancements, and added value. 

The connected home is one of the areas that is taking the most advantage of voice technologies. An interconnected smart home ecosystem allows for remote access and real-time monitoring of devices, however voice-enabled control systems are taking smart home automation to the next level. Smart home hubs like Amazon Echo, Google Nest and Samsung SmartThings allow users to use simple voice commands to manage connected devices – from lights to appliances, climate control, doors, showers and more – all from a single interface.

Voice assistants are getting smarter thanks to a combination of different technological advances: on the one hand, the evolution of natural language processing that allows sentiment analysis and understanding of the general context; on the other, improvements in artificial intelligence and machine learning that drive personalized experiences and finally, the increase in the ubiquity of voice-controlled IoT devices.

When device algorithms respond to requests, they learn at the same time. The more a person interacts with voice-activated devices, the more trends and patterns the system identifies based on the information it receives. This data can then be used to determine user preferences and tastes, which is a long-term selling point for making a home smarter.

These voice command devices are rapidly evolving, for example, to sense more than preferences and tastes. Google and Amazon seek to integrate voice-enabled artificial intelligence capable of analyzing and responding to human emotions. While the full scope of what this will look like is not yet clear, the foundation of this project lies in devices being able to identify and adapt to a user's motivations and concerns, much like the revolutionary interaction the main character has in the movie “Her” with OS1, an operating system designed to adapt and evolve like a human being, doing all communication through voice commands and soon turning from just a voice assistant to a love interest of the protagonist.

The second generation of acoustic recognition systems for smart devices will be able to distinguish the context that it listens to. Eventually, IoT devices will trigger an alarm when they hear the sound of broken window glass or wake up parents after hearing a baby or child cry at night, opening up huge market potential for new uses and applications. . Therefore, the strategy of capturing new types of data combined with higher levels of machine learning will be key. 

By Julio Cesar Blanco – April 3, 2023

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