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Gravity: Offline Language Learning Voice Recognition Sensor for micro:bit / Arduino / ESP32 - I2C & UART
- $16.50 3+ items
- $16.00 5+ items
- $15.50 10+ items
Introduction
The Offline Speech Recognition Module is an efficient solution ideal for human-computer interaction, machine learning, voice assistants, and smart home voice control projects. It is easy to use and compatible with Arduino, micro:bit, and ESP32, with detailed tutorials provided. It offers plug-and-play functionality through I2C and UART. The module features 121 built-in command words commonly used in education and smart home settings and supports 17 customized commands (e.g., recording a cat's meow for an automatic feeder). The module is highly integrated, including an onboard speaker and microphone, providing real-time voice feedback.
Easy to Use
The offline voice module is simple and compatible with existing platforms like Arduino UNO, micro:bit, and ESP32, with detailed Arduino IDE tutorials and Makecode tutorials. It supports plug-and-play through I2C and UART communication methods, allowing easy integration into projects.
121 Ready-to-Use Words
The built-in commands are commonly used in educational and smart home scenarios, allowing for immediate use without any configuration, such as "Play music," "Open the door," "Turn on the light," and "Close the window." Here is the full list of command words.
Self-Learning Function
The self-learning function is user-friendly, allowing users to add 17 customized command words. Any language or sound can be trained as a command, providing great flexibility for interactive audio projects.
Teaching the device new commands is simple. Activate the learning mode with the wake-up word, then say "Learning command word," and repeat the desired command three times. After these steps, the device will have learned the new command. Detailed instructions are provided to ensure an easy learning process.
No Internet Connection, More Secure
Users need not worry about their conversations being recorded and uploaded to the cloud. The module functions seamlessly in outdoor projects, schools, and other environments with unstable networks. Unlike existing online voice assistants that rely on cloud platforms and require internet access, potentially compromising device data privacy during use.
High Integration, Saving More Space
The offline voice module integrates an onboard speaker and microphone. High integration saves space and eliminates the hassle of complicated wiring, enhancing the project's neatness and stability.
Real-Time Voice Feedback
Users can immediately receive recognition results during use, improving user experience and convenience.
The Offline Speech Recognition Module is an easy-to-use, highly integrated solution perfect for various projects, offering 121 built-in commands, 17 customized commands, real-time voice feedback, and secure offline operation without the need for an internet connection.
Version History & Important Information
Note: DFRobot warehouses stock both V1.0 and V1.1 of this module. You may receive either version. Rest assured, both versions deliver the same core speech recognition functionality, performance, and key features outlined in this product description.
V1.1 (May 8, 2025):
This version includes minor iterative refinements focused on physical handling and assembly convenience:
V1.0 (March 2023):
The original robust and fully capable module. It provides the complete suite of offline speech recognition features and offers a highly effective and reliable user experience.
Version Update of Gravity: Offline Language Learning Voice Recognition Sensor
Features
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Review
Nov 08, 2025
Outstanding voice recognition module! The Gravity: Offline Language Learning Voice Recognition Sensor is very responsive and works perfectly without any internet connection. I tested it with an ESP32 and Arduino — setup was straightforward using I²C, and the UART interface works just as well. It recognizes commands quickly, even in slightly noisy environments, and the custom training feature is a big plus. This module is ideal for offline IoT devices, smart robots, or home automation projects where privacy and low latency are essential. Great performance, clear documentation, and typical DFRobot quality — highly recommended!
Jun 27, 2024
DFRobot has a robust wiki that goes in great detail for their products, including this module. The GitHub contains the Arduino library and an example so you can deploy this in minutes.
Included JST connector is nice as having to buy them when not included can be irritating.
Got up and running with an ESP32 I had lying around in less than 5 minutes and had serial output immediately. (SDA corresponds to GPIO21, SCL corresponds to GPIO22 in case you're planning on using an ESP)
I plan on integrating this into some projects I plan to give as gifts, eliminating the ridiculousness of having to pair everything with WiFi and have an internet connection. I'm also debating integrating it into my ESPHome setup.
Recognition works well and range is better than expected (expect many meters of range in a clear sound environment). Occasional false/failed recognitions in noise saturated environments, but that's to be expected.
Onboard learning behaves exactly as described on wiki and is self contained to the module. Simple and doesn't require programming at all.
DFRobot has a lot of resources available to tinkerers and plenty of community projects to inspire you on your next project if you ever get lost or confused.
Nov 08, 2025
Fantastic module for offline voice control! The Gravity: Offline Language Learning Voice Recognition Sensor works perfectly with Arduino and ESP32 boards. It recognizes commands quickly and accurately, even without an internet connection — a big advantage for privacy-focused or remote IoT projects. The I²C and UART interfaces make integration simple, and custom training allows you to define your own commands easily. I tested it in a smart home prototype, and it responded instantly to voice inputs. Reliable performance, clear documentation, and great build quality from DFRobot. Highly recommended for robotics and IoT enthusiasts!