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azure-ai-voicelive-dotnet

Build real-time voice assistants in .NET with Azure AI. Covers two-way audio communication, text and audio responses, detecting when a speaker finishes, and calling functions to connect conversations with external services.

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Azure AI Voice Live SDK for .NET. Build real-time voice AI applications with bidirectional WebSocket communication.

연동 도구AzureOpenAI

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이럴 때 유용합니다

  • Build a real-time voice assistant in .NET
  • Configure voices and detect when speakers finish
  • Connect voice conversations to external services
  • Handle audio, text, and error events

포함된 파일(1)

  • SKILL.md8.5 KB

SKILL.md(원문)

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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 TypeClassExample
Azure StandardAzureStandardVoice"en-US-AvaNeural"
Azure HDAzureStandardVoice"en-US-Ava:DragonHDLatestNeural"
Azure CustomAzureCustomVoiceCustom voice with endpoint ID

Supported Models

ModelDescription
gpt-4o-realtime-previewGPT-4o with real-time audio
gpt-4o-mini-realtime-previewLightweight, fast interactions
phi4-mm-realtimeCost-effective multimodal

Key Types Reference

TypePurpose
VoiceLiveClientMain client for creating sessions
VoiceLiveSessionActive WebSocket session
VoiceLiveSessionOptionsSession configuration
AzureStandardVoiceStandard Azure voice provider
AzureSemanticVadTurnDetectionVoice activity detection
VoiceLiveFunctionDefinitionFunction tool definition
UserMessageItemUser text message
FunctionCallOutputItemFunction call response
SessionUpdateResponseAudioDeltaAudio chunk event
SessionUpdateResponseTextDeltaText chunk event

Best Practices

  1. Always set both modalities — Include Text and Audio for voice assistants
  2. Use AzureSemanticVadTurnDetection — Provides natural conversation flow
  3. Configure appropriate silence duration — 500ms typical to avoid premature cutoffs
  4. Use using statement — Ensures proper session disposal
  5. Handle all event types — Check for errors, audio, text, and function calls
  6. 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

SDKPurposeInstall
Azure.AI.VoiceLiveReal-time voice (this SDK)dotnet add package Azure.AI.VoiceLive
Microsoft.CognitiveServices.SpeechSpeech-to-text, text-to-speechdotnet add package Microsoft.CognitiveServices.Speech
NAudioAudio capture/playbackdotnet add package NAudio

Reference Links

ResourceURL
NuGet Packagehttps://www.nuget.org/packages/Azure.AI.VoiceLive
API Referencehttps://learn.microsoft.com/dotnet/api/azure.ai.voicelive
GitHub Sourcehttps://github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.VoiceLive
Quickstarthttps://learn.microsoft.com/azure/ai-services/speech-service/voice-live-quickstart

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

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