技能 人工智能 Azure AI实时语音对话SDK

Azure AI实时语音对话SDK

v20260424
azure-ai-voicelive-java
这是一个用于Java开发的SDK,用于实现与Azure AI助手的实时、双向语音对话。它通过WebSocket技术支持低延迟流媒体通信,并集成了高级功能,如语音活动检测、降噪处理和多种AI音色选择。非常适用于构建专业的语音机器人和交互式语音应用。
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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/
AZURE_VOICELIVE_API_KEY=<your-api-key>

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.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

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

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.
信息
Category 人工智能
Name azure-ai-voicelive-java
版本 v20260424
大小 7.49KB
更新时间 2026-04-25
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