Agent skill

azure-ai-voicelive-java

Azure AI VoiceLive SDK for Java. Real-time bidirectional voice conversations with AI assistants using WebSocket. Triggers: "VoiceLiveClient java", "voice assistant java", "real-time voice java", "audio streaming java", "voice activity detection java".

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Install this agent skill to your Project

npx add-skill https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-java/skills/azure-ai-voicelive-java

SKILL.md

Azure AI VoiceLive SDK for Java

Real-time, bidirectional voice conversations with AI assistants using WebSocket technology.

Installation

xml
<dependency>
    <groupId>com.azure</groupId>
    <artifactId>azure-ai-voicelive</artifactId>
    <version>1.0.0-beta.2</version>
</dependency>

Environment Variables

bash
AZURE_VOICELIVE_ENDPOINT=https://<resource>.openai.azure.com/
AZURE_VOICELIVE_API_KEY=<your-api-key>

Authentication

API Key

java
import com.azure.ai.voicelive.VoiceLiveAsyncClient;
import com.azure.ai.voicelive.VoiceLiveClientBuilder;
import com.azure.core.credential.AzureKeyCredential;

VoiceLiveAsyncClient client = new VoiceLiveClientBuilder()
    .endpoint(System.getenv("AZURE_VOICELIVE_ENDPOINT"))
    .credential(new AzureKeyCredential(System.getenv("AZURE_VOICELIVE_API_KEY")))
    .buildAsyncClient();

DefaultAzureCredential (Recommended)

java
import com.azure.identity.DefaultAzureCredentialBuilder;

VoiceLiveAsyncClient client = new VoiceLiveClientBuilder()
    .endpoint(System.getenv("AZURE_VOICELIVE_ENDPOINT"))
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildAsyncClient();

Key Concepts

Concept Description
VoiceLiveAsyncClient Main entry point for voice sessions
VoiceLiveSessionAsyncClient Active WebSocket connection for streaming
VoiceLiveSessionOptions Configuration for session behavior

Audio Requirements

  • Sample Rate: 24kHz (24000 Hz)
  • Bit Depth: 16-bit PCM
  • Channels: Mono (1 channel)
  • Format: Signed PCM, little-endian

Core Workflow

1. Start Session

java
import reactor.core.publisher.Mono;

client.startSession("gpt-4o-realtime-preview")
    .flatMap(session -> {
        System.out.println("Session started");
        
        // Subscribe to events
        session.receiveEvents()
            .subscribe(
                event -> System.out.println("Event: " + event.getType()),
                error -> System.err.println("Error: " + error.getMessage())
            );
        
        return Mono.just(session);
    })
    .block();

2. Configure Session Options

java
import com.azure.ai.voicelive.models.*;
import java.util.Arrays;

ServerVadTurnDetection turnDetection = new ServerVadTurnDetection()
    .setThreshold(0.5)                    // Sensitivity (0.0-1.0)
    .setPrefixPaddingMs(300)              // Audio before speech
    .setSilenceDurationMs(500)            // Silence to end turn
    .setInterruptResponse(true)           // Allow interruptions
    .setAutoTruncate(true)
    .setCreateResponse(true);

AudioInputTranscriptionOptions transcription = new AudioInputTranscriptionOptions(
    AudioInputTranscriptionOptionsModel.WHISPER_1);

VoiceLiveSessionOptions options = new VoiceLiveSessionOptions()
    .setInstructions("You are a helpful AI voice assistant.")
    .setVoice(BinaryData.fromObject(new OpenAIVoice(OpenAIVoiceName.ALLOY)))
    .setModalities(Arrays.asList(InteractionModality.TEXT, InteractionModality.AUDIO))
    .setInputAudioFormat(InputAudioFormat.PCM16)
    .setOutputAudioFormat(OutputAudioFormat.PCM16)
    .setInputAudioSamplingRate(24000)
    .setInputAudioNoiseReduction(new AudioNoiseReduction(AudioNoiseReductionType.NEAR_FIELD))
    .setInputAudioEchoCancellation(new AudioEchoCancellation())
    .setInputAudioTranscription(transcription)
    .setTurnDetection(turnDetection);

// Send configuration
ClientEventSessionUpdate updateEvent = new ClientEventSessionUpdate(options);
session.sendEvent(updateEvent).subscribe();

3. Send Audio Input

java
byte[] audioData = readAudioChunk(); // Your PCM16 audio data
session.sendInputAudio(BinaryData.fromBytes(audioData)).subscribe();

4. Handle Events

java
session.receiveEvents().subscribe(event -> {
    ServerEventType eventType = event.getType();
    
    if (ServerEventType.SESSION_CREATED.equals(eventType)) {
        System.out.println("Session created");
    } else if (ServerEventType.INPUT_AUDIO_BUFFER_SPEECH_STARTED.equals(eventType)) {
        System.out.println("User started speaking");
    } else if (ServerEventType.INPUT_AUDIO_BUFFER_SPEECH_STOPPED.equals(eventType)) {
        System.out.println("User stopped speaking");
    } else if (ServerEventType.RESPONSE_AUDIO_DELTA.equals(eventType)) {
        if (event instanceof SessionUpdateResponseAudioDelta) {
            SessionUpdateResponseAudioDelta audioEvent = (SessionUpdateResponseAudioDelta) event;
            playAudioChunk(audioEvent.getDelta());
        }
    } else if (ServerEventType.RESPONSE_DONE.equals(eventType)) {
        System.out.println("Response complete");
    } else if (ServerEventType.ERROR.equals(eventType)) {
        if (event instanceof SessionUpdateError) {
            SessionUpdateError errorEvent = (SessionUpdateError) event;
            System.err.println("Error: " + errorEvent.getError().getMessage());
        }
    }
});

Voice Configuration

OpenAI Voices

java
// Available: ALLOY, ASH, BALLAD, CORAL, ECHO, SAGE, SHIMMER, VERSE
VoiceLiveSessionOptions options = new VoiceLiveSessionOptions()
    .setVoice(BinaryData.fromObject(new OpenAIVoice(OpenAIVoiceName.ALLOY)));

Azure Voices

java
// Azure Standard Voice
options.setVoice(BinaryData.fromObject(new AzureStandardVoice("en-US-JennyNeural")));

// Azure Custom Voice
options.setVoice(BinaryData.fromObject(new AzureCustomVoice("myVoice", "endpointId")));

// Azure Personal Voice
options.setVoice(BinaryData.fromObject(
    new AzurePersonalVoice("speakerProfileId", PersonalVoiceModels.PHOENIX_LATEST_NEURAL)));

Function Calling

java
VoiceLiveFunctionDefinition weatherFunction = new VoiceLiveFunctionDefinition("get_weather")
    .setDescription("Get current weather for a location")
    .setParameters(BinaryData.fromObject(parametersSchema));

VoiceLiveSessionOptions options = new VoiceLiveSessionOptions()
    .setTools(Arrays.asList(weatherFunction))
    .setInstructions("You have access to weather information.");

Best Practices

  1. Use async client — VoiceLive requires reactive patterns
  2. Configure turn detection for natural conversation flow
  3. Enable noise reduction for better speech recognition
  4. Handle interruptions gracefully with setInterruptResponse(true)
  5. Use Whisper transcription for input audio transcription
  6. Close sessions properly when conversation ends

Error Handling

java
session.receiveEvents()
    .doOnError(error -> System.err.println("Connection error: " + error.getMessage()))
    .onErrorResume(error -> {
        // Attempt reconnection or cleanup
        return Flux.empty();
    })
    .subscribe();

Reference Links

Resource URL
GitHub Source https://github.com/Azure/azure-sdk-for-java/tree/main/sdk/ai/azure-ai-voicelive
Samples https://github.com/Azure/azure-sdk-for-java/tree/main/sdk/ai/azure-ai-voicelive/src/samples

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