{"slug":"azure-ai-voicelive-ts","title":"azure-ai-voicelive-ts","summary":"Azure AI Voice Live SDK for JavaScript/TypeScript. Build real-time voice AI applications with bidirectional WebSocket communication. Use for voice assistants, conversational AI, real-time speech-to-speech, and voice-enabled chatbots in Node.js or browser environments. Triggers: \"","platform":"GitHub Copilot","tags":[],"authorName":"Ciza","authorSlug":"ciza","score":0,"source":"github","price":null,"verified":false,"createdAt":"2026-08-12T21:05:16.306059Z","repo":{"url":"https://github.com/microsoft/skills","stars":3052,"forks":351,"license":"MIT","updatedAt":"2026-09-24T16:38:17Z"},"bodyHtml":"
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name: azure-ai-voicelive-ts\ndescription: |\nAzure AI Voice Live SDK for JavaScript/TypeScript. Build real-time voice AI applications with bidirectional WebSocket communication. Use for voice assistants, conversational AI, real-time speech-to-speech, and voice-enabled chatbots in Node.js or browser environments. Triggers: \"voice live\", \"real-time voice\", \"VoiceLiveClient\", \"VoiceLiveSession\", \"voice assistant TypeScript\", \"bidirectional audio\", \"speech-to-speech JavaScript\".\nlicense: MIT\nmetadata:\nauthor: Microsoft\nversion: \"1.0.0\"\npackage: '@azure/ai-voicelive'

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@azure/ai-voicelive (JavaScript/TypeScript)

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Real-time voice AI SDK for building bidirectional voice assistants with Azure AI in Node.js and browser environments.

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Installation

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npm install @azure/ai-voicelive @azure/identity\n# TypeScript users\nnpm install @types/node\n
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Current Version: 1.0.0-beta.3

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Supported Environments:

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Environment Variables

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AZURE_VOICELIVE_ENDPOINT=https://<resource>.cognitiveservices.azure.com\n# Optional: API key if not using Entra ID\nAZURE_VOICELIVE_API_KEY=<your-api-key>\n# Optional: Logging\nAZURE_LOG_LEVEL=info\nAZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production\n
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Authentication

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Microsoft Entra Token Credential (Recommended)

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import { DefaultAzureCredential, ManagedIdentityCredential } from \"@azure/identity\";\nimport { VoiceLiveClient } from \"@azure/ai-voicelive\";\n\n// Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>\nconst credential = new DefaultAzureCredential({requiredEnvVars: [\"AZURE_TOKEN_CREDENTIALS\"]});\n// Or use a specific credential directly in production:\n// See https://learn.microsoft.com/javascript/api/overview/azure/identity-readme?view=azure-node-latest#credential-classes\n// const credential = new ManagedIdentityCredential();\nconst endpoint = \"https://your-resource.cognitiveservices.azure.com\";\n\nconst client = new VoiceLiveClient(endpoint, credential);\n
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API Key

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import { AzureKeyCredential } from \"@azure/core-auth\";\nimport { VoiceLiveClient } from \"@azure/ai-voicelive\";\n\nconst endpoint = \"https://your-resource.cognitiveservices.azure.com\";\nconst credential = new AzureKeyCredential(\"your-api-key\");\n\nconst client = new VoiceLiveClient(endpoint, credential);\n
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Client Hierarchy

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VoiceLiveClient\n└── VoiceLiveSession (WebSocket connection)\n    ├── updateSession()      → Configure session options\n    ├── subscribe()          → Event handlers (Azure SDK pattern)\n    ├── sendAudio()          → Stream audio input\n    ├── addConversationItem() → Add messages/function outputs\n    └── sendEvent()          → Send raw protocol events\n
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Quick Start

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import { DefaultAzureCredential } from \"@azure/identity\";\nimport { VoiceLiveClient } from \"@azure/ai-voicelive\";\n\nconst credential = new DefaultAzureCredential({requiredEnvVars: [\"AZURE_TOKEN_CREDENTIALS\"]});\nconst endpoint = process.env.AZURE_VOICELIVE_ENDPOINT!;\n\n// Create client and start session\nconst client = new VoiceLiveClient(endpoint, credential);\nconst session = await client.startSession(\"gpt-4o-mini-realtime-preview\");\n\n// Configure session\nawait session.updateSession({\n  modalities: [\"text\", \"audio\"],\n  instructions: \"You are a helpful AI assistant. Respond naturally.\",\n  voice: {\n    type: \"azure-standard\",\n    name: \"en-US-AvaNeural\",\n  },\n  turnDetection: {\n    type: \"server_vad\",\n    threshold: 0.5,\n    prefixPaddingMs: 300,\n    silenceDurationMs: 500,\n  },\n  inputAudioFormat: \"pcm16\",\n  outputAudioFormat: \"pcm16\",\n});\n\n// Subscribe to events\nconst subscription = session.subscribe({\n  onResponseAudioDelta: async (event, context) => {\n    // Handle streaming audio output\n    const audioData = event.delta;\n    playAudioChunk(audioData);\n  },\n  onResponseTextDelta: async (event, context) => {\n    // Handle streaming text\n    process.stdout.write(event.delta);\n  },\n  onInputAudioTranscriptionCompleted: async (event, context) => {\n    console.log(\"User said:\", event.transcript);\n  },\n});\n\n// Send audio from microphone\nfunction sendAudioChunk(audioBuffer: ArrayBuffer) {\n  session.sendAudio(audioBuffer);\n}\n
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Session Configuration

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await session.updateSession({\n  // Modalities\n  modalities: [\"audio\", \"text\"],\n  \n  // System instructions\n  instructions: \"You are a customer service representative.\",\n  \n  // Voice selection\n  voice: {\n    type: \"azure-standard\",  // or \"azure-custom\", \"openai\"\n    name: \"en-US-AvaNeural\",\n  },\n  \n  // Turn detection (VAD)\n  turnDetection: {\n    type: \"server_vad\",      // or \"azure_semantic_vad\"\n    threshold: 0.5,\n    prefixPaddingMs: 300,\n    silenceDurationMs: 500,\n  },\n  \n  // Audio formats\n  inputAudioFormat: \"pcm16\",\n  outputAudioFormat: \"pcm16\",\n  \n  // Tools (function calling)\n  tools: [\n    {\n      type: \"function\",\n      name: \"get_weather\",\n      description: \"Get current weather\",\n      parameters: {\n        type: \"object\",\n        properties: {\n          location: { type: \"string\" }\n        },\n        required: [\"location\"]\n      }\n    }\n  ],\n  toolChoice: \"auto\",\n});\n
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Event Handling (Azure SDK Pattern)

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The SDK uses a subscription-based event handling pattern:

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const subscription = session.subscribe({\n  // Connection lifecycle\n  onConnected: async (args, context) => {\n    console.log(\"Connected:\", args.connectionId);\n  },\n  onDisconnected: async (args, context) => {\n    console.log(\"Disconnected:\", args.code, args.reason);\n  },\n  onError: async (args, context) => {\n    console.error(\"Error:\", args.error.message);\n  },\n  \n  // Session events\n  onSessionCreated: async (event, context) => {\n    console.log(\"Session created:\", context.sessionId);\n  },\n  onSessionUpdated: async (event, context) => {\n    console.log(\"Session updated\");\n  },\n  \n  // Audio input events (VAD)\n  onInputAudioBufferSpeechStarted: async (event, context) => {\n    console.log(\"Speech started at:\", event.audioStartMs);\n  },\n  onInputAudioBufferSpeechStopped: async (event, context) => {\n    console.log(\"Speech stopped at:\", event.audioEndMs);\n  },\n  \n  // Transcription events\n  onConversationItemInputAudioTranscriptionCompleted: async (event, context) => {\n    console.log(\"User said:\", event.transcript);\n  },\n  onConversationItemInputAudioTranscriptionDelta: async (event, context) => {\n    process.stdout.write(event.delta);\n  },\n  \n  // Response events\n  onResponseCreated: async (event, context) => {\n    console.log(\"Response started\");\n  },\n  onResponseDone: async (event, context) => {\n    console.log(\"Response complete\");\n  },\n  \n  // Streaming text\n  onResponseTextDelta: async (event, context) => {\n    process.stdout.write(event.delta);\n  },\n  onResponseTextDone: async (event, context) => {\n    console.log(\"\\n--- Text complete ---\");\n  },\n  \n  // Streaming audio\n  onResponseAudioDelta: async (event, context) => {\n    const audioData = event.delta;\n    playAudioChunk(audioData);\n  },\n  onResponseAudioDone: async (event, context) => {\n    console.log(\"Audio complete\");\n  },\n  \n  // Audio transcript (what assistant said)\n  onResponseAudioTranscriptDelta: async (event, context) => {\n    process.stdout.write(event.delta);\n  },\n  \n  // Function calling\n  onResponseFunctionCallArgumentsDone: async (event, context) => {\n    if (event.name === \"get_weather\") {\n      const args = JSON.parse(event.arguments);\n      const result = await getWeather(args.location);\n      \n      await session.addConversationItem({\n        type: \"function_call_output\",\n        callId: event.callId,\n        output: JSON.stringify(result),\n      });\n      \n      await session.sendEvent({ type: \"response.create\" });\n    }\n  },\n  \n  // Catch-all for debugging\n  onServerEvent: async (event, context) => {\n    console.log(\"Event:\", event.type);\n  },\n});\n\n// Clean up when done\nawait subscription.close();\n
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Function Calling

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// Define tools in session config\nawait session.updateSession({\n  modalities: [\"audio\", \"text\"],\n  instructions: \"Help users with weather information.\",\n  tools: [\n    {\n      type: \"function\",\n      name: \"get_weather\",\n      description: \"Get current weather for a location\",\n      parameters: {\n        type: \"object\",\n        properties: {\n          location: {\n            type: \"string\",\n            description: \"City and state or country\",\n          },\n        },\n        required: [\"location\"],\n      },\n    },\n  ],\n  toolChoice: \"auto\",\n});\n\n// Handle function calls\nconst subscription = session.subscribe({\n  onResponseFunctionCallArgumentsDone: async (event, context) => {\n    if (event.name === \"get_weather\") {\n      const args = JSON.parse(event.arguments);\n      const weatherData = await fetchWeather(args.location);\n      \n      // Send function result\n      await session.addConversationItem({\n        type: \"function_call_output\",\n        callId: event.callId,\n        output: JSON.stringify(weatherData),\n      });\n      \n      // Trigger response generation\n      await session.sendEvent({ type: \"response.create\" });\n    }\n  },\n});\n
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Voice Options

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Voice TypeConfigExample
Azure Standard{ type: \"azure-standard\", name: \"...\" }\"en-US-AvaNeural\"
Azure Custom{ type: \"azure-custom\", name: \"...\", endpointId: \"...\" }Custom voice endpoint
Azure Personal{ type: \"azure-personal\", speakerProfileId: \"...\" }Personal voice clone
OpenAI{ type: \"openai\", name: \"...\" }\"alloy\", \"echo\", \"shimmer\"
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Supported Models

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ModelDescriptionUse Case
gpt-4o-realtime-previewGPT-4o with real-time audioHigh-quality conversational AI
gpt-4o-mini-realtime-previewLightweight GPT-4oFast, efficient interactions
phi4-mm-realtimePhi multimodalCost-effective applications
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Turn Detection Options

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// Server VAD (default)\nturnDetection: {\n  type: \"server_vad\",\n  threshold: 0.5,\n  prefixPaddingMs: 300,\n  silenceDurationMs: 500,\n}\n\n// Azure Semantic VAD (smarter detection)\nturnDetection: {\n  type: \"azure_semantic_vad\",\n}\n\n// Azure Semantic VAD (English optimized)\nturnDetection: {\n  type: \"azure_semantic_vad_en\",\n}\n\n// Azure Semantic VAD (Multilingual)\nturnDetection: {\n  type: \"azure_semantic_vad_multilingual\",\n}\n
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Audio Formats

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FormatSample RateUse Case
pcm1624kHzDefault, high quality
pcm16-8000hz8kHzTelephony
pcm16-16000hz16kHzVoice assistants
g711_ulaw8kHzTelephony (US)
g711_alaw8kHzTelephony (EU)
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Key Types Reference

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TypePurpose
VoiceLiveClientMain client for creating sessions
VoiceLiveSessionActive WebSocket session
VoiceLiveSessionHandlersEvent handler interface
VoiceLiveSubscriptionActive event subscription
ConnectionContextContext for connection events
SessionContextContext for session events
ServerEventUnionUnion of all server events
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Error Handling

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import {\n  VoiceLiveError,\n  VoiceLiveConnectionError,\n  VoiceLiveAuthenticationError,\n  VoiceLiveProtocolError,\n} from \"@azure/ai-voicelive\";\n\nconst subscription = session.subscribe({\n  onError: async (args, context) => {\n    const { error } = args;\n    \n    if (error instanceof VoiceLiveConnectionError) {\n      console.error(\"Connection error:\", error.message);\n    } else if (error instanceof VoiceLiveAuthenticationError) {\n      console.error(\"Auth error:\", error.message);\n    } else if (error instanceof VoiceLiveProtocolError) {\n      console.error(\"Protocol error:\", error.message);\n    }\n  },\n  \n  onServerError: async (event, context) => {\n    console.error(\"Server error:\", event.error?.message);\n  },\n});\n
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Logging

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import { setLogLevel } from \"@azure/logger\";\n\n// Enable verbose logging\nsetLogLevel(\"info\");\n\n// Or via environment variable\n// AZURE_LOG_LEVEL=info\n
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Browser Usage

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// Browser requires bundler (Vite, webpack, etc.)\nimport { VoiceLiveClient } from \"@azure/ai-voicelive\";\nimport { InteractiveBrowserCredential } from \"@azure/identity\";\n\n// Use browser-compatible credential\nconst credential = new InteractiveBrowserCredential({\n  clientId: \"your-client-id\",\n  tenantId: \"your-tenant-id\",\n});\n\nconst client = new VoiceLiveClient(endpoint, credential);\n\n// Request microphone access\nconst stream = await navigator.mediaDevices.getUserMedia({ audio: true });\nconst audioContext = new AudioContext({ sampleRate: 24000 });\n\n// Process audio and send to session\n// ... (see samples for full implementation)\n
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Best Practices

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    \n
  1. Use DefaultAzureCredential for local development; use ManagedIdentityCredential or WorkloadIdentityCredential for production — Never hardcode API keys
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  2. Set both modalities — Include [\"text\", \"audio\"] for voice assistants
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  3. Use Azure Semantic VAD — Better turn detection than basic server VAD
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  4. Handle all error types — Connection, auth, and protocol errors
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  5. Clean up subscriptions — Call subscription.close() when done
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  6. Use appropriate audio format — PCM16 at 24kHz for best quality
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Reference Links

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ResourceURL
npm Packagehttps://www.npmjs.com/package/@azure/ai-voicelive
GitHub Sourcehttps://github.com/Azure/azure-sdk-for-js/tree/main/sdk/ai/ai-voicelive
Sampleshttps://github.com/Azure/azure-sdk-for-js/tree/main/sdk/ai/ai-voicelive/samples
API Referencehttps://learn.microsoft.com/javascript/api/@azure/ai-voicelive
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