microsoft/cognitive-services-speech-sdk-js
Microsoft Azure Cognitive Services Speech SDK for JavaScript
What it solves
It provides a way for developers to integrate Microsoft Cognitive Services speech capabilities into applications built with JavaScript, allowing them to handle speech-to-text and text-to-speech tasks.
How it works
The SDK acts as a client library that connects to Microsoft's cloud-based speech services. It is designed to be compatible with both web browser environments and Node.js server-side environments.
Who it’s for
JavaScript developers who want to add voice recognition or speech synthesis features to their web apps or Node.js applications.
Highlights
- Supports both browser and Node.js environments.
- Provides prebuilt packages for easy installation via npm.
- Includes a mechanism to enable or disable telemetry for service performance monitoring.
Related
- Project
Azure-Samples/Cognitive-Speech-TTSA Microsoft‑maintained repo of SDK and REST code samples showing how to use Azure Cognitive Services Speech (Text‑to‑Speech), with links to customer stories, blog posts, and research. Ideal for developers who need ready‑to‑run examples for realistic, multilingual synthetic voices, custom neural voices, and related Azure Speech features.
- Project
Azure-Samples/cognitive-services-speech-sdkA collection of code samples for the Microsoft Cognitive Services Speech SDK, demonstrating how to implement speech recognition, translation, and synthesis across multiple platforms and languages.
- Project
elevenlabs/elevenlabs-jsThe official Node.js SDK for ElevenLabs, enabling developers to integrate lifelike AI voice synthesis, real-time audio streaming, and voice-powered AI agents into their applications.
- Project
watson-developer-cloud/node-sdkA Node.js client library for integrating IBM Watson AI services, providing simplified authentication and API access for tools like Watson Assistant and Discovery.
- Project
lmstudio-ai/lmstudio-jsThe official TypeScript/JavaScript SDK for LM Studio, enabling developers to integrate local LLMs into applications with advanced model management and agentic capabilities.