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We use smart devices every day by using voice search. The first step was voice search on phones. After that, we got used to wearables, voice assistants, car speakers, and more. Several cloud platforms, like Apple's Siri, Google's Assistant, Microsoft's Cortana, and Amazon's Alexa, get credit for this, but the real hero is Edge Computing.
Voice search interfaces are made possible in large part by this technology. Inside the devices, much research is done to figure out how to handle the users' voices, languages, and accents. Let's talk about how voice search works in more depth.
Keyword tracking
Voice search is becoming an important part of digital marketing, so keywords that most people use are growing increasingly important. As a result, when you ask a speech-enabled gadget to search, it does not always record your voice and query the cloud if someone is instructing it on what to do.
Recording and sending it back and forth will take a lot more time, adding to the latency and slowing down the response time. Not only that, but it would also be a waste of privacy, energy, and resources.
Most voice-adaptive interfaces use a method called "wake-word detection," which only needs a small amount of processing power at the edge or on the device itself. This is how the devices handle the signals from the microphones so that the system doesn't get messed up. This methodology employs very little power and allows smart devices with batteries to be used longer.
During the main part of wake-word detection, digital signal processing (DSP) looks for a match with the most-expected word. Also, it tells the whole system how much computing power is needed to record sound, understand the language and accent, track voice, and send it after it has been compressed.
Noise separation from the main commands
After it has found the keywords, the smart device that can be controlled by voice listens more carefully. The system must now figure out the meaning of voice commands. Well, that depends on how clear your voice and accent are, which may be harder to accomplish on the street, at a restaurant, at a party, or in a space with everyone talking.
Several methods of edge computing can tell the main user's voice from the rest of the noise. For example, beam-forming techniques use the device's multiple microphones to focus on where the user speaks. This could be like a virtual microphone with directional capabilities.
Voice tracking algorithms in the smart device change the signals from the different microphones when the user moves. This maintains the emphasis on where the voice is emerging from. Now, voice-enabled devices have better technology that lets them process commands from multiple microphones by canceling the noise around them. This is also how noise-blocking headphones work.
The technology that eliminates echo and noise is also constructed into smart speakers. It cancels out all other speakers' and music's sounds with microphone signals, so the smart speaker can receive voice instructions even when there is much noise around. When you tell the smart speaker to do something, it can do it.
Smart devices with artificial intelligence
Edge computing has enabled AI to be used on smart devices, such as those that can be controlled by voice. With this method, the device can use its language memory computation to handle basic offline commands even when it's not connected to the internet.
As a result, even when the device isn't linked to the web, you may set a reminder or alarm, turn up or down the lights and security alarm, and adjust the temperature. With more advanced technology, the voice can also verify a user's identity on smart devices.
With this feature, random people won't be able to tell your voice-processing device to do things you don't want. You can also instruct the AI-powered voice-processing device to recognize your baby's cries or the audio of something breaking so it can sound an alarm to let you know.
By adding cameras that work with your voice, you can get better results and more clear information. AI is getting better, so there are more interesting ways to use it. People want smart devices to be the greatest at high-tech edge processing, so they use more heterogeneous processors.
Architectures become increasingly diversified when more resources must be packed into a single chip. Putting all of this together tends to help make the best use of energy and computer resources, which saves money. All devices with a voice interface can be used to do tasks.
Making Final Statement
Voice search is something we're used to using on our phones as well as smart speakers. But as edge computing and AI improve, virtual voice interfaces can control many more devices.
The potential of the edge with cloud computing together can contribute to a better world where gadgets can do many useful things offline. With 5G, smart devices will also be quicker to respond. Technology will keep improving, making us sit around more and less.