Audio – Classify audio to detect sounds and trigger an action in your web app.

Lipsync by youtube AI-powered challenge rates how closely your lip syncing matches the song. Using Google’s AI technology, TensorFlow.js detects landmarks on your face using machine learning running in the browser.

Preloading model

Transfer learning

Using TensorFlow.js, we can develop a robust framework that enables the seamless integration of speech command recognition into web-based applications. Your platform leverages the deep learning capabilities of TensorFlow.js to train and deploy highly accurate models for detecting and interpreting spoken commands.

The Speech Command Recognizer is a JavaScript module that enables the recognition of spoken commands comprised of simple isolated English words from a small vocabulary. The default vocabulary includes the following words: the ten digits from “zero” to “nine”, “up”, “down”, “left”, “right”, “go”, “stop”, “yes”, “no”, as well as the additional categories of “unknown word” and “background noise”.

Online streaming recognition, during which the library automatically opens an audio input channel using the browser’s getUserMedia and WebAudio APIs (requesting permission from user) and performs real-time recognition on the audio input.

Offline recognition, in which you provide a pre-constructed TensorFlow.js Tensor object or a Float32Array and the recognizer will return the recognition results.

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Our dedicated team of experts is committed to supporting developers throughout development. We provide comprehensive documentation, code samples, and tutorials that simplify the integration of speech command recognition into web and mobile applications. Additionally, our active community fosters collaboration and knowledge sharing, enabling developers to stay updated with the latest advancements in this field.

Join us on our journey as we continue to push the boundaries of speech command recognition using TensorFlow.js. Together, we can create compelling applications that enable users to interact with technology using their natural voice, revolutionizing the way we interact with digital systems.