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Optimized for Embedded Voice Applications: Ideal for IoT, wearable, and embedded voice solutions, the Nicla Voice can run AI algorithms directly on the device. This reduces latency and ensures that sensitive voice data is processed locally, providing enhanced privacy and lower dependency on cloud-based systems.
Edge AI for Voice Recognition: The Arduino Nicla Voice is a powerful, compact board designed for real-time voice recognition and audio processing. Powered by the Qualcomm QCC5100 chip and equipped with a high-quality microphone, it enables local processing of audio data for smart voice applications like speech-to-text, sound classification, and voice commands without relying on cloud services.
Compact Design with Integrated Sensors: Despite its small size, the Nicla Voice includes integrated features like a microphone array for improved voice capture, and built-in motion sensors (accelerometer and gyroscope). These capabilities allow the board to perform voice control, gesture recognition, and even context-aware interactions in a wide range of applications.
【Speech recognition broadcast function】 Based on CSK4002, it is an AlSoC with high performance, strong computing power and low power consumption for the development and design of the AloT field. The comprehensive wake-up rate is 95%, and the comprehensive recognition rate is 93%. The user wakes up the device and speaks the command word, and the device responds after recognition; the command word supports a variety of product scenarios and supports 85 voice command recognition.
【Offline Voice Interaction Processing】 The voice interaction module is equipped with an offline voice chip, which is free of programming and easy to use. The human-computer interaction function can be realized by obtaining the recognition result through the serial port; in the offline state, the relevant processing is performed according to the content of the command word, or the content information is transmitted to the host computer for further processing. related processing.
【360° Effective Pickup】 The front end of the voice module adopts a dual-microphone array algorithm, which can realize user voice pickup within 5m of the 360° far field. Equipped with automatic vocal gain, it can be adaptively adjusted according to the user's volume to ensure that the overall hearing of the audio after noise reduction is consistent.
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Voice Recognition Module V3: Users need to train the module first before let it recognizing any voice command
On V3, voice commands are stored in one large group like a library. Any 7 voice commands in the library could be imported into recognizer. It means 7 commands are effective at the same time
【Professional-level voice processing】Built-in CI1302 chip, equipped with neural network processor, integrated echo cancellation and environmental noise reduction technology, the measured recognition accuracy is as high as 99%, effectively suppressing environmental noise and echo interference, ensuring stable operation in complex scenarios.
【Highly customizable voice commands】Supports 110+ preset commands. Users can edit command content online and generate firmware burning through web pages. It supports multi-language commands, which is convenient and efficient to operate and meet the needs of global products.The burning software only supports Windows.
【Fully compatible development support】Provides STM32, ESP32, Ard-uin-o, Raspberry-Pi, Jetson Nano, Jetson Orin and other development board materials, supports ROS1/ROS2 system SDK, and meets the development needs of multiple scenarios such as smart hardware, robots, and homes.
Unleash Creativity with VC-02 Kit: Elevate your smart home and gadgets to the next level with the VC-02-Kit AI Intelligent Offline Voice Module. Integrated with a CH340C serial to USB chip, it offers fundamental debugging interfaces and USB upgrade options, making it an indispensable tool for hobbyists and innovators alike
Intuitive Design, Enhanced Interaction: Experience seamless control with the VC-02's built-in wake-up and mood lights, providing clear status and control indications. This Voice Recognition Module is designed to add a touch of sophistication
Engineered for Excellence: The VC-02 Development Board is powered by a 32bit RISC architecture core, supplemented with a DSP instruction set tailored for signal processing and voice recognition. It boasts an FPU for floating-point operations and an FFT accelerator, ensuring robust performance for complex projects
Support calculation: support up to 1024 points of FFT IFFT complex calculation or 2048 points of real FFT IFFT calculation.
High-quality materials: 32bit RISC core, 240M operating frequency, support for DSP instruction set and FPU floating point arithmetic unit.
Applicable scenarios: Used in smart homes, all kinds of smart home appliances, 86 boxes, toys, lamps, industry, internet of things, cars, security and lighting, and other products that require voice control.
Wide Compatibility: WonderEcho AI voice module's Type-C and I2C interfaces make it fully compatible with Arduino, Raspberry Pi, STM32, ESP32, Jetson, microbit, Scratch, and ROS, enabling integration into a variety of development environments.
High-Precision Voice Recognition and Broadcasting: WonderEcho AI voice module seamlessly integrates voice recognition and broadcasting functions, achieving a recognition accuracy of up to 98%. It supports both English & Chinese keywords, offering robust capabilities for intelligent voice applications.
Advanced Neural Network Processor: Powered by a neural network processor, WonderEcho AI voice module supports convolutional neural network (CNN) operations, greatly improving both the speed and accuracy of voice recognition.
This high-sensitivity microphone sensor module is suitable for voice recognition systems and can capture and transmit sound signals. It can be used for voice-controlled switch applications such as voice-controlled lights and voice-controlled electronic devices. In addition, in environmental monitoring, it can be used to detect noise levels or sound frequencies.
The Microphone Sound Sensor, we provide here, is in size of: Working Voltage: DC 3-24 V Output Form: Digital and Analog Output Model: KY-038 Number of Pins:4 In the package of: 4 x Voice Sound Detection Sensor
High sensitivity: The sound sensor module has high sensitivity and can accurately capture sound signals in the environment. Easy interface: Simple connection to various microcontrollers or electronic devices for easy integration and use. Stability: Provides stable performance and reliable sound detection function.
[Versatile Applications] Quickly learn and verify offline voice control for various peripherals, such as relays, LED lights, and PWM dimming.
[Universal Io Ports] All the IO ports of the voice module are seamlessly integrated into this development board, allowing for easy connection to breadboards.
[Low Power Consumption] The offline voice recognition development board boasts low power consumption, making it efficient and energy-saving.
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