Agent skill
azure-ai-voicelive-dotnet
Azure AI Voice Live SDK for .NET. 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. Triggers: "voice live", "real-time voice", "VoiceLiveClient", "VoiceLiveSession", "voice assistant .NET", "bidirectional audio", "speech-to-speech".
Install this agent skill to your Project
npx add-skill https://github.com/aiskillstore/marketplace/tree/main/skills/sickn33/azure-ai-voicelive-dotnet
SKILL.md
Azure.AI.VoiceLive (.NET)
Real-time voice AI SDK for building bidirectional voice assistants with Azure AI.
Installation
dotnet add package Azure.AI.VoiceLive
dotnet add package Azure.Identity
dotnet add package NAudio # For audio capture/playback
Current Versions: Stable v1.0.0, Preview v1.1.0-beta.1
Environment Variables
AZURE_VOICELIVE_ENDPOINT=https://<resource>.services.ai.azure.com/
AZURE_VOICELIVE_MODEL=gpt-4o-realtime-preview
AZURE_VOICELIVE_VOICE=en-US-AvaNeural
# Optional: API key if not using Entra ID
AZURE_VOICELIVE_API_KEY=<your-api-key>
Authentication
Microsoft Entra ID (Recommended)
using Azure.Identity;
using Azure.AI.VoiceLive;
Uri endpoint = new Uri("https://your-resource.cognitiveservices.azure.com");
DefaultAzureCredential credential = new DefaultAzureCredential();
VoiceLiveClient client = new VoiceLiveClient(endpoint, credential);
Required Role: Cognitive Services User (assign in Azure Portal → Access control)
API Key
Uri endpoint = new Uri("https://your-resource.cognitiveservices.azure.com");
AzureKeyCredential credential = new AzureKeyCredential("your-api-key");
VoiceLiveClient client = new VoiceLiveClient(endpoint, credential);
Client Hierarchy
VoiceLiveClient
└── VoiceLiveSession (WebSocket connection)
├── ConfigureSessionAsync()
├── GetUpdatesAsync() → SessionUpdate events
├── AddItemAsync() → UserMessageItem, FunctionCallOutputItem
├── SendAudioAsync()
└── StartResponseAsync()
Core Workflow
1. Start Session and Configure
using Azure.Identity;
using Azure.AI.VoiceLive;
var endpoint = new Uri(Environment.GetEnvironmentVariable("AZURE_VOICELIVE_ENDPOINT"));
var client = new VoiceLiveClient(endpoint, new DefaultAzureCredential());
var model = "gpt-4o-mini-realtime-preview";
// Start session
using VoiceLiveSession session = await client.StartSessionAsync(model);
// Configure session
VoiceLiveSessionOptions sessionOptions = new()
{
Model = model,
Instructions = "You are a helpful AI assistant. Respond naturally.",
Voice = new AzureStandardVoice("en-US-AvaNeural"),
TurnDetection = new AzureSemanticVadTurnDetection()
{
Threshold = 0.5f,
PrefixPadding = TimeSpan.FromMilliseconds(300),
SilenceDuration = TimeSpan.FromMilliseconds(500)
},
InputAudioFormat = InputAudioFormat.Pcm16,
OutputAudioFormat = OutputAudioFormat.Pcm16
};
// Set modalities (both text and audio for voice assistants)
sessionOptions.Modalities.Clear();
sessionOptions.Modalities.Add(InteractionModality.Text);
sessionOptions.Modalities.Add(InteractionModality.Audio);
await session.ConfigureSessionAsync(sessionOptions);
2. Process Events
await foreach (SessionUpdate serverEvent in session.GetUpdatesAsync())
{
switch (serverEvent)
{
case SessionUpdateResponseAudioDelta audioDelta:
byte[] audioData = audioDelta.Delta.ToArray();
// Play audio via NAudio or other audio library
break;
case SessionUpdateResponseTextDelta textDelta:
Console.Write(textDelta.Delta);
break;
case SessionUpdateResponseFunctionCallArgumentsDone functionCall:
// Handle function call (see Function Calling section)
break;
case SessionUpdateError error:
Console.WriteLine($"Error: {error.Error.Message}");
break;
case SessionUpdateResponseDone:
Console.WriteLine("\n--- Response complete ---");
break;
}
}
3. Send User Message
await session.AddItemAsync(new UserMessageItem("Hello, can you help me?"));
await session.StartResponseAsync();
4. Function Calling
// Define function
var weatherFunction = new VoiceLiveFunctionDefinition("get_current_weather")
{
Description = "Get the current weather for a given location",
Parameters = BinaryData.FromString("""
{
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state or country"
}
},
"required": ["location"]
}
""")
};
// Add to session options
sessionOptions.Tools.Add(weatherFunction);
// Handle function call in event loop
if (serverEvent is SessionUpdateResponseFunctionCallArgumentsDone functionCall)
{
if (functionCall.Name == "get_current_weather")
{
var parameters = JsonSerializer.Deserialize<Dictionary<string, string>>(functionCall.Arguments);
string location = parameters?["location"] ?? "";
// Call external service
string weatherInfo = $"The weather in {location} is sunny, 75°F.";
// Send response
await session.AddItemAsync(new FunctionCallOutputItem(functionCall.CallId, weatherInfo));
await session.StartResponseAsync();
}
}
Voice Options
| Voice Type | Class | Example |
|---|---|---|
| Azure Standard | AzureStandardVoice |
"en-US-AvaNeural" |
| Azure HD | AzureStandardVoice |
"en-US-Ava:DragonHDLatestNeural" |
| Azure Custom | AzureCustomVoice |
Custom voice with endpoint ID |
Supported Models
| Model | Description |
|---|---|
gpt-4o-realtime-preview |
GPT-4o with real-time audio |
gpt-4o-mini-realtime-preview |
Lightweight, fast interactions |
phi4-mm-realtime |
Cost-effective multimodal |
Key Types Reference
| Type | Purpose |
|---|---|
VoiceLiveClient |
Main client for creating sessions |
VoiceLiveSession |
Active WebSocket session |
VoiceLiveSessionOptions |
Session configuration |
AzureStandardVoice |
Standard Azure voice provider |
AzureSemanticVadTurnDetection |
Voice activity detection |
VoiceLiveFunctionDefinition |
Function tool definition |
UserMessageItem |
User text message |
FunctionCallOutputItem |
Function call response |
SessionUpdateResponseAudioDelta |
Audio chunk event |
SessionUpdateResponseTextDelta |
Text chunk event |
Best Practices
- Always set both modalities — Include
TextandAudiofor voice assistants - Use
AzureSemanticVadTurnDetection— Provides natural conversation flow - Configure appropriate silence duration — 500ms typical to avoid premature cutoffs
- Use
usingstatement — Ensures proper session disposal - Handle all event types — Check for errors, audio, text, and function calls
- Use DefaultAzureCredential — Never hardcode API keys
Error Handling
if (serverEvent is SessionUpdateError error)
{
if (error.Error.Message.Contains("Cancellation failed: no active response"))
{
// Benign error, can ignore
}
else
{
Console.WriteLine($"Error: {error.Error.Message}");
}
}
Audio Configuration
- Input Format:
InputAudioFormat.Pcm16(16-bit PCM) - Output Format:
OutputAudioFormat.Pcm16 - Sample Rate: 24kHz recommended
- Channels: Mono
Related SDKs
| SDK | Purpose | Install |
|---|---|---|
Azure.AI.VoiceLive |
Real-time voice (this SDK) | dotnet add package Azure.AI.VoiceLive |
Microsoft.CognitiveServices.Speech |
Speech-to-text, text-to-speech | dotnet add package Microsoft.CognitiveServices.Speech |
NAudio |
Audio capture/playback | dotnet add package NAudio |
Reference Links
| Resource | URL |
|---|---|
| NuGet Package | https://www.nuget.org/packages/Azure.AI.VoiceLive |
| API Reference | https://learn.microsoft.com/dotnet/api/azure.ai.voicelive |
| GitHub Source | https://github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.VoiceLive |
| Quickstart | https://learn.microsoft.com/azure/ai-services/speech-service/voice-live-quickstart |
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
perigon-backend
Perigon ASP.NET Core + EF Core + Aspire conventions
perigon-agent
Pointers for Copilot/agents to apply Perigon conventions
perigon-angular
Angular 21+ standalone/Material/signal conventions for Perigon WebApp
fastapi-mastery
Comprehensive FastAPI development skill covering REST API creation, routing, request/response handling, validation, authentication, database integration, middleware, and deployment. Use when working with FastAPI projects, building APIs, implementing CRUD operations, setting up authentication/authorization, integrating databases (SQL/NoSQL), adding middleware, handling WebSockets, or deploying FastAPI applications. Triggered by requests involving .py files with FastAPI code, API endpoint creation, Pydantic models, or FastAPI-specific features.
context7-efficient
Token-efficient library documentation fetcher using Context7 MCP with 86.8% token savings through intelligent shell pipeline filtering. Fetches code examples, API references, and best practices for JavaScript, Python, Go, Rust, and other libraries. Use when users ask about library documentation, need code examples, want API usage patterns, are learning a new framework, need syntax reference, or troubleshooting with library-specific information. Triggers include questions like "Show me React hooks", "How do I use Prisma", "What's the Next.js routing syntax", or any request for library/framework documentation.
browser-use
Browser automation using Playwright MCP. Navigate websites, fill forms, click elements, take screenshots, and extract data. Use when tasks require web browsing, form submission, web scraping, UI testing, or any browser interaction.
Didn't find tool you were looking for?