![]() ![]() To initialize Picovoice in our app, we’re going to need a Picovoice AccessKey, a Porcupine wake word model, and a Rhino context model. For our example command, the Rhino inference result would look like this: Rhino uses an embedded grammar to determine the meaning of the command without transcribing it to text - it instead returns a RhinoInference object. In this phrase, Porcupine identifies the wake word “Pico Clock” and Rhino infers the intent of the command that follows. The combination of these two recognition engines allows us to offer a familiar voice experience to our users: a wake word followed by a command that our app will execute - e.g: The Picovoice platform encapsulates the Porcupine Wake Word engine and the Rhino Speech-to-Intent. Simply install the following packages from npm to get started: npm i npm i npm i npm i 2 - Initialize the Speech Recognition Platform On how to configure your applications, please refer to the README.md of each example.The Picovoice React Native SDK is going to give us the tools we need to add voice recognition on the edge. To run ESP-Skainet, you need to have an ESP32 or ESP32-S3 development board which integrates an audio input module. Quick Start with ESP-Skainet Hardware Preparation Our two-mic Audio Front-End (AFE) have been qualified as a “Software Audio Front-End Solution” for Amazon Alexa Built-in devices. Audio Front EndĮspressif Audio Front-End AFE integrates AEC (Acoustic Echo Cancellation), VAD (Voice Activity Detection),BSS (Blind Source Separation) and NS (Noise Suppression). With this model, you can easily add your own speech commands, eliminating the need to train model again.Ĭurrently, Espressif MultiNet supports up to 200 Chinese or English speech commands, such as “打开空调” (Turn on the air conditioner) and “打开卧室灯” (Turn on the bedroom light). Speech Commands RecognitionĮspressif's speech command recognition model MultiNet is specially designed to provide a flexible offline speech command recognition model. ![]() ![]() For details on how to customize your own wake words, please see Espressif Speech Wake Words Customization Process. Wake Word EngineĮspressif wake word engine WakeNet is specially designed to provide a high performance and low memory footprint wake word detection algorithm for users, which enables devices always wait for wake words, such as "Alexa", “天猫精灵” (Tian Mao Jing Ling), and “小爱同学” (Xiao Ai Tong Xue).Ĭurrently, Espressif has not only provided an official wake word "Hi, Lexin" to the public for free but also allows customized wake words. The input audio stream can come from any way of providing voice, such as MIC, wav/pcm files in flash/SD Card. In general, the ESP-Skainet features will be supported, as shown below: With ESP-Skainet, you can easily build up wake word detection and speech command recognition applications. OverviewĮSP-Skainet supports the development of wake word detection and speech commands recognition applications based around Espressif Systems' ESP32 series chip in the most convenient way. The Latest models will be deployed on ESP32-S3 first. ESP32-S3 is recommend to run speech commands recognition, which supports AI instructions and high-speed octal SPI PSRAM. ESP-Skainet is Espressif's intelligent voice assistant, which currently supports the Wake Word Engine and Speech Commands Recognition. ![]()
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