Azure Ai Voicelive Dotnet
Azure Ai Voicelive Dotnet is an data AI skill with a core value of |. It
helps developers solve real-world problems in the data domain, boosting
efficiency, automating repetitive tasks, and optimizing workflows.
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Quick Facts
mkdir -p ./skills/azure-ai-voicelive-dotnet && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/azure-ai-voicelive-dotnet/SKILL.md -o ./skills/azure-ai-voicelive-dotnet/SKILL.md Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# 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 =🎯 Best For
- Claude users
- Data professionals
- Analytics teams
- Researchers
💡 Use Cases
- Data pipeline auditing
- Query optimization
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Azure Ai Voicelive Dotnet to Your Work
Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.
- 4
Review and Refine
Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.
❓ Frequently Asked Questions
How do I install Azure Ai Voicelive Dotnet?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/azure-ai-voicelive-dotnet/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Ignoring data quality
AI analysis inherits all data quality issues — profile your data first.