Amazon‘s website has introduced a Software Audio Front End (AFE) Development Kit section that lists software algorithms that optimize sound detection in noisy environments. The latest addition is the Amazon Alexa recently certified Espressif audio front end or ESP AFE algorithm for shorts.
Low resource consumption
Espressif’s AFE algorithms are optimized, as they take advantage of Espressif’s AI accelerator that is available in the ESP32-S3 SoC. Espressif’s AFE algorithms consume just 12-20% of CPU and around 460 KB of memory, including 220 KB of internal memory and 240 KB of external memory. This provides sufficient headroom for customer applications on the ESP32-S3 SoC.
Espressif’s AFE algorithms offer an easy and intuitive API for customer applications, so that their performance can change as dynamically as it is required. The distance between the two microphones can be between 20-80 mm, which allows considerable flexibility for the hardware design of developers’ end-products.
Source: https://www.espressif.com/en/solutions/audio-solutions/esp-afe
The Espressif AFE algorithm was certified by Amazon after achieving excellent performance in long-range Alexa testing. In most cases, in low signal-to-noise scenarios, the wakeup rate reaches 100% and the speech recognition rate exceeds 90%.
Industrial use of ESP32-based solutions
One of industrial IoT devices, supporting Espressif’s ESP32 technology is eModGATE from TECHBASE. Economical, ESP32-based solution can serve as an end-point in any installation or works well as a gateway, gathering data from scattered sensor mesh across the installation. For more information and also Raspberry Pi based solutions check Industrial IoT Shop with all the configuration options for eModGATE.
