The Future of Keyword Spotting:
A Deep Dive into Edge AI and PIMIC’s Listen™ Chip
By Carl DeSalvo Date Published: September 16th, 2024 16 min read
Introduction
Voice interaction is becoming an integral part of our daily lives, with devices like smart speakers, home appliances, and wearables increasingly relying on the power of our spoken words to operate. At the heart of this transformation is a technology known as keyword spotting (KWS), which enables devices to detect specific wake words and phrases in continuous audio streams. 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 expanding its reach to edge computing — where data processing occurs locally on devices, without relying on cloud servers. This shift is vital for reducing latency, enhancing privacy, and improving power efficiency. This article will explore what keyword spotting is, how it’s being applied at the edge, and what the future holds for this technology. We’ll also highlight the revolutionary capabilities of PIMIC’s Listen chip, a breakthrough solution in the world of edge-based keyword spotting.
What is Keyword Spotting?
At its core, keyword spotting is a technology that listens for specific words or phrases in an audio stream to trigger a response from a device. These words are often known as wake words — think of saying “Hey Siri” or “OK Google” to get a smartphone’s attention. Keyword spotting can also include a wider range of commands, such as "Turn on the lights" or "Set a timer for 10 minutes."
The key to excellent KWS is high accuracy and the ability to continuously monitor audio input in a low-power state until it detects the specified keyword, allowing the system to remain in standby mode until needed. This is particularly important for devices such as wearables and IoT devices, where battery life and low power consumption are crucial.
The Shift to Edge AI
As keyword spotting becomes more common, there’s a growing need to process these voice commands locally on devices — what is known as edge AI. Traditionally, many voice-enabled devices rely on cloud computing, where audio data is sent to a remote server for processing. This works well in some scenarios, but it has limitations, including potential delays (latency), privacy concerns, and a reliance on constant internet connectivity.
Edge AI changes the game by performing data processing directly on the device itself. For keyword spotting, this means a device can listen for wake words and respond in real time, without needing to send data to the cloud. This offers several benefits:
Reduced latency: Responses are almost instantaneous because no data needs to travel to the cloud and back.
Improved privacy: Since audio data stays on the device, there’s less risk of personal information being intercepted or stored remotely.
Lower power consumption: Processing at the edge can mean devices can operate much more efficiently especially if the correct architecture is employed. This is mandatory for environments where power is at a premium.
A great example of edge-based keyword spotting is a smart home appliance like a refrigerator. With keyword spotting integrated, the appliance can listen for specific voice commands, such as “Make the fridge 2 degrees cooler,” and respond instantly. Because the processing happens locally, it doesn’t need to be connected to the internet to function. This is especially useful in settings where internet access may be unreliable, or where users are concerned about privacy.
Market Trends for Keyword Spotting at the Edge
The demand for keyword spotting at the edge is growing rapidly, driven by several key factors. According to industry projections, the global voice recognition market is expected to grow significantly over the next five years, with keyword spotting and edge computing playing an increasingly important role.
One of the primary drivers of this growth is the rise of IoT (Internet of Things) devices, which require low-power solutions to operate efficiently. Keyword spotting is perfect for IoT because it allows these devices to be controlled hands-free, while conserving energy by only waking up when a command is detected.
Another driver is the increasing adoption of voice-controlled wearables like smartwatches and fitness trackers. Consumers want the convenience of voice control, but battery life is a top priority. This creates a strong demand for low-power, edge-based keyword spotting solutions that can deliver functionality without draining the battery.
Lastly, the growth of smart home appliances is pushing the need for voice interfaces that work locally. From washing machines to ovens, consumers expect the convenience of voice control, but don’t always want to be connected to the cloud. Edge-based keyword spotting provides the ideal solution, allowing appliances to operate based on voice commands without needing an internet connection.
Practical Applications of Keyword Spotting
There are a variety of real-world applications for keyword spotting at the edge, each highlighting the flexibility and potential of the technology:
Wearables: Devices like smartwatches or health monitors can stay in low-power standby mode and activate when a voice command is detected. This allows users to control features hands-free, such as setting a timer or checking their step count, without sacrificing battery life.
Smart Home Appliances: Imagine a washing machine that responds to voice commands like “Start the wash” without needing to be connected to the internet. The keyword spotting system runs locally, so the appliance can function offline while still providing a convenient user experience.
Home Automation Devices: Smart light switches, thermostats, and security cameras are all becoming more intelligent. With keyword spotting at the edge, these devices can respond to voice commands immediately, enabling a truly smart home experience without always being connected to the cloud.
PIMIC’s Listen Chip – Revolutionizing Keyword Spotting
At the forefront of this edge AI transformation is PIMIC’s Listen™ chip, a breakthrough solution for ultra-low-power keyword spotting. The Listen chip has been specifically designed for edge devices, offering unmatched performance in a compact, power-efficient package.
Here are some of the key features of the Listen chip:
Small Size: The chip is less than 1.2mm², making it ideal for compact devices like wearables and remote controls.
Ultra-Low Power Consumption: To illustrate the efficiency of the Listen chip, we can calculate how long it can operate continuously (24/7/365) on different battery types. The average power consumption of the Listen chip is 50 microwatts (0.00005 watts). Using four common battery types, the table below shows the estimated battery life in months:
Battery Life Estimations for the Listen Chip
| Battery Type | Watt Hours (Wh) | Estimated Duration (Months) |
| 9 Volt Battery | 4.8 Wh | 164.4 months (approx. 13.7 years) |
| AA Battery | 2.5 Wh | 85.6 months (approx. 7.1 years) |
| AAA Battery | 1.2 Wh | 41.1 months (approx. 3.4 years) |
| CR2032 Button Battery | 0.24 Wh | 8.2 months (approx. 0.68 years) |
No Internet Connection Required: Listen processes voice commands locally, eliminating the need for cloud connectivity and enhancing privacy.
Supports 32 Wake and Keywords: This allows for the recognition of a range of voice commands and keywords.
Easy Integration: The Listen chip is integrated inside the microphone package and requires only a few extra pins for data transmission and control, simplifying the design process for manufacturers.
Practical Use Cases for the Listen Chip
Smartwatches: The Listen chip allows smartwatches to operate in ultra-low power mode, only waking up when a voice command is detected. This not only extends battery life but also enhances usability for hands-free tasks.
Smart Glasses: Listen’s main advantage for smart glasses is its wake word capability. These devices have powerful hardware but struggle with battery life. Listen’s low-power requirements while waiting for a wake word solves this problem. Once the wake word is detected, Listen wakes the glasses, allowing their systems to take over. In this case, Listen’s keyword recognition isn’t needed; its job is simply to save battery life until the device is activated.
Home Appliances: Integrating Listen into home appliances like refrigerators or ovens enhances the user interface by making voice control simple and easy to use. Removing the requirement of an internet connection ensures that anyone, no matter where the appliance is installed, can benefit from the voice-controlled interface while simplifying the appliance’s installation.
Energy Efficiency Impact
Consider the energy savings possible if Listen were integrated into devices like Google’s Home Mini, Amazon’s Echo, or other electronic devices placed in standby mode. These devices typically consume between 0.5 to 5 watts in standby mode. Using Listen, their standby power consumption could drop to just 50 microwatts. Extrapolating this to a wider scale, if Listen were used in only 1% of the ~144 million U.S. homes each having 4 such devices on average, would save ~1.58 billion watts of power per year, in the United States alone.
The Future of Keyword Spotting and Edge AI
As edge AI continues to evolve, keyword spotting will play an even greater role in enabling voice interaction across various devices. Future technological advancements are expected to include expanded language support, even more accurate voice recognition, and further reductions in power consumption.
PIMIC is at the forefront of these developments, with the Listen chip already setting new standards for efficiency, ease of integration, and privacy in keyword spotting at the edge. As more industries adopt voice control technology, PIMIC’s solutions will help drive innovation in smart homes, wearables, and healthcare.
Conclusion
Keyword spotting is not just about recognizing wake words anymore — it’s about enabling smarter, more efficient interactions across the devices we use everyday. With the rise of edge AI, solutions like PIMIC’s Listen chip are transforming how we interact with technology, offering ultra-low-power, privacy-focused, and easy-to-integrate solutions that push the boundaries of voice-controlled devices. The future of keyword spotting is here, and it’s only getting more exciting. If you want to see PIMIC’s Listen chip working live at CES2025 please join us January 7th through the 10th, at the Las Vegas Convention Center, North Hall – Booth 9628.
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Author's Bio
Carl DeSalvo, a BSEE graduate from the University of Illinois, has had a distinguished Electronic Design Automation (EDA) career. He's held key positions at major firms like Cadence Design Systems and Synopsys and contributed to various startups. Carl spent three years in Europe supporting backend ASIC design for major electronics corporations.
Upon returning to the US, Carl transitioned to Sales and Marketing, eventually founding EDATechForce, LLC. This sales representative firm partnered with over 20 companies during its decade-long operation.
Currently, Carl is Vice President of Business Development and Sales at PIMIC, Inc., an AI startup developing innovative silicon solutions for neural network architectures. His experience continues to drive growth in the AI industry.
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