The Gravity: Offline Voice Recognition Sensor
To be eligible, you must meet ALL of the following requirements:
1. Your project is free from inappropriate content.
2. Your project is an original work and you have full and independent intellectual property rights to the work and the right to use it for this program.
Hardware/Software Build Requirements
Your project must include the DFRobot Voice Recognition Sensor.
The following types of content will not be considered eligible item content.
1. Unboxing content.
2. Content involves a lot of descriptions of the product, its performance, etc.
3. Content involves a lot of descriptions that are not related to the product or this project.
For Videos projects:
1. No less than 5mins.
2. Video should be clear and bright. [No blurriness and distortions that may compromise the quality of the submission
For Text-Pic projects
1. Your project should have a complete structure, and the body of the article should be at least 500 words, including a project name, images, a bill of materials (BOM), full instructions, and relevant resources (schematics, code, CAD).
2. Your project should be written in English.
1. Do I need to pay for the trial application?
No, DFRobot will offer the products free of charge. Still, you may need to pay the potential tariff due to different countries' and regions policies.
2. How will I know the application result?
We will announce the application winners on July 21st, 2023.
3. Can I submit a repeat application?
Please note that you only have one opportunity to submit your application, if you make multiple applications, the information from the first application will be used.
4. Can I use the products you offer for other purposes?
The products we offer to you are intended for use in the production of projects only. Profit-making activities such as the secondary sale of this product are not permitted.
This Gravity: Offline Voice Recognition Sensor is built around an offline voice recognition chip, which can be directly used without an internet connection. It comes with 121 built-in fixed command words and supports the addition of 17 custom command words. Any sound could be trained as a command, such as whistling, snapping, or even cat meows, which brings great flexibility to interactive audio projects.
The module features a dual microphone design with better noise resistance and a longer recognition distance, making it relatively accurate and reliable even in noisy environments. It comes with a built-in speaker and an external speaker interface for real-time voice feedback of recognition results. The module uses both I2C and UART communication methods and supports various 3.3V or 5V controllers, including the micro:bit, Arduino (Arduino UNO, Arduino Leonardo, Arduino MEGA), Raspberry Pi, FireBeetle series, and more.
This voice recognition module provides a reliable and flexible voice interaction solution for makers and electronics enthusiasts, and it can be applied to any applications where voice control or interaction is desirable, such as all kinds of smart home appliances, toys, lamps, and robotics projects.
Difference between offline and online voice recognition
An important factor in voice recognition is the voice database, which is used as comparative data during the recognition process. Online voice databases are stored in the cloud and have a very large amount of data, while offline voice databases are local and have limited space.
FEATURESSelf-learning function: Control the module to learn command words by the voice, and any audio can be trained as a commandSupport I2C and UART, with a Gravity interfaceCompatible with 3.3V/5VBuilt-in with 121 commonly-used fixed command wordsThe module has a built-in speaker and an interface for an external speaker, which can provide real-time voice feedback on recognition resultsEquipped with power indicator (red) and recognition status indicator (blue)Dual microphones provide better noise resistance and longer recognition distanceCompatible with Arduino controllers: Arduino UNO, Arduino Leonardo, Arduino MEGA, FireBeetle series controllers, Raspberry Pi, ESP32