Azure AI VoiceLive SDK for Java

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

Installation

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

Environment Variables

AZURE_VOICELIVE_ENDPOINT=https://<resource>.openai.azure.com/ # Required for all auth methods
AZURE_VOICELIVE_API_KEY=<your-api-key> # Only required for AzureKeyCredential auth
AZURE_TOKEN_CREDENTIALS=prod  # Required only if DefaultAzureCredential is used in production

Authentication

API Key

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)

import com.azure.core.credential.TokenCredential;
import com.azure.identity.AzureIdentityEnvVars;
import com.azure.identity.DefaultAzureCredentialBuilder;
import com.azure.identity.ManagedIdentityCredentialBuilder;

TokenCredential credential = new DefaultAzureCredentialBuilder()
    .requireEnvVars(AzureIdentityEnvVars.AZURE_TOKEN_CREDENTIALS)
    .build();
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/java/api/overview/azure/identity-readme?view=azure-java-stable#credential-classes
// TokenCredential credential = new ManagedIdentityCredentialBuilder().build();

VoiceLiveAsyncClient client = new VoiceLiveClientBuilder()
    .endpoint(System.getenv("AZURE_VOICELIVE_ENDPOINT"))
    .credential(credential)
    .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

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

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

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

4. Handle Events

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

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

Azure Voices

// 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

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

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