Welcome to the Keyword Spotting Revolution: Where Intelligent Voice Interaction meets Real-World Applications

As smart devices, wearables, and consumer appliances become more sophisticated, voice interaction is rapidly emerging as the preferred interface for users. However, embedding always-on voice capabilities into energy-constrained devices presents a significant engineering challenge: how can we maintain responsiveness while minimizing power consumption?

Keyword Spotting (KWS) offers a compelling solution. By enabling devices to remain in an ultra-low-power state and only respond when specific wake words or commands are detected, KWS bridges the gap between user convenience, privacy, and energy efficiency.

This article explores how Keyword Spotting is reshaping voice interaction for edge devices, and how technologies like BrainChip’s Akida Pico are setting new standards for ultra-low-power, private, and scalable voice-enabled solutions.

What is Keyword Spotting?

Keyword Spotting (KWS) means devices detect specific wake words and phrases and interact only when there is a match. This technology powers the functionality behind familiar voice-activated systems, making them responsive and user-friendly. However, as devices evolve and user expectations grow, Keyword Spotting is now occurring locally on devices, without cloud connectivity.

How to Determine when Device interaction is Needed

If the keywords are not recognized, the device does not attempt to process any data, which elongates battery life and provides an additional layer of user privacy.

Why Keyword Spotting?

Keyword Spotting is a technology that listens for specific words or phrases in an audio stream, triggering a response from a device. Once known only for waking up a device service that routes the rest of the voice from your home or smartphone device to a server in the cloud, Keyword Spotting can be deployed locally to interpret a wide set of in context commands, such as “lock the door” or “set the microwave for 1 minute.”

The key is the device’s ability to locally monitor audio input in a low-power state until it detects the specified keyword, allowing the system to save battery or compute power until needed, which is particularly important for devices such as wearables and other IoT devices. Having a small library of key words enables local control of a device without any other interface.

Key benefits of Keyword Spotting:

• Reduces user latency

Responses are nearly instantaneous, providing a natural voice interface, without the need for round trips to the cloud and back.

• Enhances privacy

Audio data stays on the device, there’s no risk of personal information being eavesdropped on by remote servers.

• Significantly reduces the cost of ownership

Local edge processing allows devices to operate without relying on cloud connectivity, reducing operational costs.

There are a host of examples of how this can benefit users in scenarios like a vehicle,
where commands like “turn on the lights” or “check for maintenance” offer a better
experience than searching for switches or menus. It enables instant, connection-free
responses, which is crucial for safety.

Market Needs For
Voice Control at the Edge

IoT (Internet of Things) devices, which are low-power solutions for the edge, can be controlled hands-free, potentially eliminating a touch display and visual attention.

Wearables like smartwatches, fitness trackers and medical monitors where the convenience of voice control is a top priority.

Smart home appliances, from lights, thermostats, security cameras, microwaves, laundry, cooking and coffee machines, consumers enjoy the convenience of voice control, but prefer to avoid subscription costs or having their daily activities monitored.

Why Energy Efficiency is Important

Many home devices have high standby power due to displays and microcontrollers constantly scanning for inputs and adding cloud-based voice interactivity would further increase this power consumption. Akida Pico drastically reduces the energy consumed by devices in standby mode, cutting power use from watts to microwatts—a thousand-fold decrease.

This innovation can significantly lower the global power load across billions of devices.

Where is this going in the Future?

Future advancements will feature expanded language support, improved voice recognition, and seamless integration of language processing with edge LLMs, eliminating the need for user guides and maintenance manuals.

Akida is at the forefront of these developments, with Akida Pico setting the bar for efficiency, cost of ownership, ease of integration, and privacy for Keyword Spotting at the edge.

Integrating Voice Wake Up Functionality into your Next Chip Design

Keyword Spotting enables smarter, more efficient interactions with everyday devices.

Akida Pico, leveraging advanced TENNs state-space neural processing models at the edge, transforms products with an ultra-low-power, private, and easy-to-integrate design for natural voice control. This marks the starting point for the future of voice interaction.

Learn more about how BrainChip’s Akida Pico can transform your AI strategy and advance solutions development.