Live API 的設定選項


即使只是基本實作 Live API，您也能為使用者打造引人入勝且強大的互動體驗。您也可以視需要使用下列設定選項，進一步自訂體驗：


回覆語音和語言

您可以讓模型以特定語音回覆，並引導模型以不同語言回覆。

指定回覆語音

按一下您的Gemini API供應商，即可在這個頁面查看供應商專屬內容和程式碼。

Live API 支援 30 種不同的合成 HD 語音，每種語音都有獨特特色。展開下方區段，即可查看回覆語音選項清單，並聆聽各語音的示範。

如未指定回覆語音，預設為 Puck。

如要指定回覆語音，請在模型設定中，設定 speechConfig 物件內的語音名稱。

Swift 


// ...

let liveModel = FirebaseAI.firebaseAI(backend: .googleAI()).liveModel(
  modelName: "GEMINI_LIVE_API_MODEL_NAME",
  // Configure the model to use a specific voice for its audio response.
  generationConfig: LiveGenerationConfig(
    responseModalities: [.audio],
    speech: SpeechConfig(voiceName: "VOICE_NAME")
  )
)

// ...

Kotlin 


// ...

val model = Firebase.ai(backend = GenerativeBackend.googleAI()).liveModel(
    modelName = "GEMINI_LIVE_API_MODEL_NAME",
    // Configure the model to use a specific voice for its audio response.
    generationConfig = liveGenerationConfig {
        responseModality = ResponseModality.AUDIO
        speechConfig = SpeechConfig(voice = Voice("VOICE_NAME"))
    }
)

// ...

Java 


// ...

LiveGenerativeModel lm = FirebaseAI.getInstance(GenerativeBackend.googleAI()).liveModel(
    "GEMINI_LIVE_API_MODEL_NAME",
    // Configure the model to use a specific voice for its audio response.
    new LiveGenerationConfig.Builder()
        .setResponseModality(ResponseModality.AUDIO)
        .setSpeechConfig(new SpeechConfig(new Voice("VOICE_NAME")))
        .build()
);

// ...

Web 


// ...

const ai = getAI(firebaseApp, { backend: new GoogleAIBackend() });

const liveModel = getLiveGenerativeModel(ai, {
  model: "GEMINI_LIVE_API_MODEL_NAME",
  // Configure the model to use a specific voice for its audio response.
  generationConfig: {
    responseModalities: [ResponseModality.AUDIO],
    speechConfig: {
      voiceConfig: {
        prebuiltVoiceConfig: { voiceName: "VOICE_NAME" },
      },
    },
  },
});

// ...

Dart 


// ...

final _liveModel = FirebaseAI.googleAI().liveGenerativeModel(
  model: 'GEMINI_LIVE_API_MODEL_NAME',
  // Configure the model to use a specific voice for its audio response.
  liveGenerationConfig: LiveGenerationConfig(
    responseModalities: [ResponseModalities.audio],
    speechConfig: SpeechConfig(voiceName: 'VOICE_NAME'),
  ),
);

// ...

Unity 


// ...

var liveModel = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI()).GetLiveModel(
    modelName: "GEMINI_LIVE_API_MODEL_NAME",
    // Configure the model to use a specific voice for its audio response
    liveGenerationConfig: new LiveGenerationConfig(
        responseModalities: new[] { ResponseModality.Audio },
        speechConfig: SpeechConfig.UsePrebuiltVoice("VOICE_NAME")
    )
);

// ...

影響回覆語言

Live API 模型會自動選擇適當的回覆語言。

如要讓模型以非英文或一律以特定語言回覆，可以使用系統指示影響模型的回覆，例如：

  • 向模型強調，非英文語言可能更合適

    Listen to the speaker carefully. If you detect a non-English language, respond
in the language you hear from the speaker. You must respond unmistakably in the
speaker's language.

  • 要求模型一律以特定語言回覆

    RESPOND IN LANGUAGE. YOU MUST RESPOND UNMISTAKABLY IN LANGUAGE.


音訊輸入和輸出的轉錄稿

按一下您的Gemini API供應商，即可在這個頁面查看供應商專屬內容和程式碼。

模型回覆時，會一併提供音訊輸入內容和模型音訊回覆的轉錄稿。您可以在模型設定中調整這項設定。

  • 如要轉錄音訊輸入內容，請新增 inputAudioTranscription。

  • 如要轉錄模型的音訊回覆，請新增 outputAudioTranscription。

注意事項：

  • 您可以設定模型，讓模型傳回輸入和輸出的轉錄稿 (如下例所示)，也可以設定模型，讓模型只傳回其中一項。

  • 轉錄稿會與音訊一起串流，因此最好在每個回合中，像收集文字部分一樣收集轉錄稿。

  • 系統會根據音訊輸入和模型的音訊回覆，推論語音轉錄語言。

Swift 


// ...

let liveModel = FirebaseAI.firebaseAI(backend: .googleAI()).liveModel(
  modelName: "GEMINI_LIVE_API_MODEL_NAME",
  // Configure the model to return transcriptions of the audio input and output.
  generationConfig: LiveGenerationConfig(
    responseModalities: [.audio],
    inputAudioTranscription: AudioTranscriptionConfig(),
    outputAudioTranscription: AudioTranscriptionConfig()
  )
)

var inputTranscript: String = ""
var outputTranscript: String = ""

do {
  let session = try await liveModel.connect()
  for try await response in session.responses {
    if case let .content(content) = response.payload {
      if let inputText = content.inputAudioTranscription?.text {
        // Handle transcription text of the audio input.
        inputTranscript += inputText
      }

      if let outputText = content.outputAudioTranscription?.text {
        // Handle transcription text of the audio output.
        outputTranscript += outputText
      }

      if content.isTurnComplete {
        // Log the transcripts after the current turn is complete.
        print("Input audio: \(inputTranscript)")
        print("Output audio: \(outputTranscript)")

        // Reset the transcripts for the next turn.
        inputTranscript = ""
        outputTranscript = ""
      }
    }
  }


} catch {
  // Handle error
}

// ...

Kotlin 


// ...

val liveModel = Firebase.ai(backend = GenerativeBackend.googleAI()).liveModel(
    modelName = "GEMINI_LIVE_API_MODEL_NAME",
    // Configure the model to return transcriptions of the audio input and output.
    generationConfig = liveGenerationConfig {
        responseModality = ResponseModality.AUDIO
        inputAudioTranscription = AudioTranscriptionConfig()
        outputAudioTranscription = AudioTranscriptionConfig()
   }
)

val liveSession = liveModel.connect()

fun handleTranscription(input: Transcription?, output: Transcription?) {
    input?.text?.let { text ->
        // Handle transcription text of the audio input.
        println("Input Transcription: $text")
    }
    output?.text?.let { text ->
        // Handle transcription text of the audio output.
        println("Output Transcription: $text")
    }
}

liveSession.startAudioConversation(null, ::handleTranscription)

// ...

Java 


// ...

ExecutorService executor = Executors.newFixedThreadPool(1);

LiveGenerativeModel lm = FirebaseAI.getInstance(GenerativeBackend.googleAI()).liveModel(
    "GEMINI_LIVE_API_MODEL_NAME",
    // Configure the model to return transcriptions of the audio input and output.
    new LiveGenerationConfig.Builder()
            .setResponseModality(ResponseModality.AUDIO)
            .setInputAudioTranscription(new AudioTranscriptionConfig())
            .setOutputAudioTranscription(new AudioTranscriptionConfig())
            .build()
    );

LiveModelFutures liveModel = LiveModelFutures.from(lm);
ListenableFuture<LiveSessionFutures> sessionFuture = liveModel.connect();

Futures.addCallback(sessionFuture, new FutureCallback<LiveSessionFutures>() {
    @Override
    public void onSuccess(LiveSessionFutures ses) {
        LiveSessionFutures session = ses;
        session.startAudioConversation((Transcription input, Transcription output) -> {
            if (input != null) {
                // Handle transcription text of the audio input.
                System.out.println("Input Transcription: " + input.getText());
            }
            if (output != null) {
                // Handle transcription text of the audio output.
                System.out.println("Output Transcription: " + output.getText());
            }
            return null;
        });
    }

    @Override
    public void onFailure(Throwable t) {
        // Handle exceptions
        t.printStackTrace();
    }
}, executor);

// ...

Web 


// ...

const ai = getAI(firebaseApp, { backend: new GoogleAIBackend() });

const liveModel = getLiveGenerativeModel(ai, {
  model: 'GEMINI_LIVE_API_MODEL_NAME',
  // Configure the model to return transcriptions of the audio input and output.
  generationConfig: {
    responseModalities: [ResponseModality.AUDIO],
    inputAudioTranscription: {},
    outputAudioTranscription: {},
  },
});

const liveSession = await liveModel.connect();

liveSession.sendAudioRealtime({ data, mimeType: "audio/pcm" });

const messages = liveSession.receive();
for await (const message of messages) {
  switch (message.type) {
    case 'serverContent':
      if (message.inputTranscription) {
        // Handle transcription text of the audio input.
        console.log(`Input transcription: ${message.inputTranscription.text}`);
      }
      if (message.outputTranscription) {
        // Handle transcription text of the audio output.
        console.log(`Output transcription: ${message.outputTranscription.text}`);
      } else {
      	 // Handle other message types (modelTurn, turnComplete, interruption).
      }
    default:
      // Handle other message types (toolCall, toolCallCancellation).
  }
}

// ...

Dart 


// ...

final _liveModel = FirebaseAI.googleAI().liveGenerativeModel(
  model: 'GEMINI_LIVE_API_MODEL_NAME',
  // Configure the model to return transcriptions of the audio input and output.
  liveGenerationConfig: LiveGenerationConfig(
    responseModalities: [ResponseModalities.audio],
    inputAudioTranscription: AudioTranscriptionConfig(),
    outputAudioTranscription: AudioTranscriptionConfig(),
  ),
);

final LiveSession _session = await _liveModel.connect();

await for (final response in _session.receive()) {
  if (response.message case LiveServerContent message) {
    if (message.inputTranscription?.text case final inputText?) {
      // Handle transcription text of the audio input.
      print('Input: $inputText');
    }

    if (message.outputTranscription?.text case final outputText?) {
      // Handle transcription text of the audio output.
      print('Output: $outputText');
    }
  }
}

// ...

Unity 


// ...

var liveModel = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI()).GetLiveModel(
    modelName: "GEMINI_LIVE_API_MODEL_NAME",
    // Configure the model to return transcriptions of the audio input and output
    liveGenerationConfig: new LiveGenerationConfig(
        responseModalities: new[] { ResponseModality.Audio },
        inputAudioTranscription: new AudioTranscriptionConfig(),
        outputAudioTranscription: new AudioTranscriptionConfig()
    )
);

try
{
    var session = await liveModel.ConnectAsync();
    var stream = session.ReceiveAsync();
    await foreach (var response in stream) {
        if (response.Message is LiveSessionContent sessionContent) {
            if (!string.IsNullOrEmpty(sessionContent.InputTranscription?.Text)) {
              // handle transcription text of input audio
            }

            if (!string.IsNullOrEmpty(sessionContent.OutputTranscription?.Text)) {
              // handle transcription text of output audio
            }
        }
    }
}
catch (Exception e)
{
    // Handle error
}

// ...


語音活動偵測 (VAD)

語音活動偵測 (VAD) 可讓模型辨識使用者何時說話。這項功能可讓您隨時打斷模型，是打造自然對話體驗的關鍵。VAD 預設為啟用。

您可以自訂 VAD 的行為，包括處理中斷情形。您也可以停用自動 VAD，完全手動控制對話輪流 (例如即按即說介面)。

設定語音活動偵測 (VAD)

按一下您的Gemini API供應商，即可在這個頁面查看供應商專屬內容和程式碼。

以下範例說明如何將 realtimeInputConfig 設為模型設定的一部分，藉此自訂 VAD 行為。如要瞭解這項設定的可用設定，請參閱本節後續的表格。

Swift 


// ...

let liveModel = FirebaseAI.firebaseAI(backend: .googleAI()).liveModel(
  modelName: "GEMINI_LIVE_API_MODEL_NAME",
  generationConfig: LiveGenerationConfig(
    responseModalities: [.audio],
    // Configure voice activity detection (VAD), interruption handling, and turn coverage.
    // IMPORTANT: Example values shown here. Make sure to update for your use case.
    realtimeInputConfig: RealtimeInputConfig(
      automaticActivityDetection: ActivityDetectionConfig(
        startSensitivity: .low,
        endSensitivity: .low,
        prefixPadding: .milliseconds(20),
        silenceDuration: .milliseconds(500)
      ),
      activityHandling: .interrupt,
      turnCoverage: .onlyActivity
    )
  )
)

Kotlin 


// ...

val liveModel = Firebase.ai(backend = GenerativeBackend.googleAI()).liveModel(
    modelName = "GEMINI_LIVE_API_MODEL_NAME",
    generationConfig = liveGenerationConfig {
        responseModality = ResponseModality.AUDIO
        // Configure voice activity detection (VAD), interruption handling, and turn coverage.
        // IMPORTANT: Example values shown here. Make sure to update for your use case.
        realtimeInputConfig = realtimeInputConfig {
            automaticActivityDetection = ActivityDetectionConfig.builder()
                .setStartSensitivity(ActivityDetectionConfig.Sensitivity.LOW)
                .setEndSensitivity(ActivityDetectionConfig.Sensitivity.LOW)
                .setPrefixPaddingMs(20)
                .setSilenceDurationMs(500)
                .build()
            activityHandling = RealtimeInputConfig.ActivityHandling.INTERRUPT
            turnCoverage = RealtimeInputConfig.TurnCoverage.ONLY_ACTIVITY
        }
    }
)

Java 


// ...

LiveGenerativeModel lm = FirebaseAI.getInstance(GenerativeBackend.googleAI()).liveModel(
        "GEMINI_LIVE_API_MODEL_NAME",
        new LiveGenerationConfig.Builder()
                .setResponseModality(ResponseModality.AUDIO)
                // Configure voice activity detection (VAD), interruption handling, and turn coverage.
                // IMPORTANT: Example values shown here. Make sure to update for your use case.
                .setRealtimeInputConfig(RealtimeInputConfig.builder()
                        .setAutomaticActivityDetection(ActivityDetectionConfig.builder()
                                .setStartSensitivity(ActivityDetectionConfig.Sensitivity.LOW)
                                .setEndSensitivity(ActivityDetectionConfig.Sensitivity.LOW)
                                .setPrefixPaddingMs(20)
                                .setSilenceDurationMs(500)
                                .build())
                        .setActivityHandling(RealtimeInputConfig.ActivityHandling.INTERRUPT)
                        .setTurnCoverage(RealtimeInputConfig.TurnCoverage.ONLY_ACTIVITY)
                        .build())
                .build()
);

Web 

Not yet supported for Web apps - check back soon!

Dart 


// ...

final _liveModel = FirebaseAI.googleAI().liveGenerativeModel(
  model: 'GEMINI_LIVE_API_MODEL_NAME',
  liveGenerationConfig: LiveGenerationConfig(
    responseModalities: [ResponseModalities.audio],
    // Configure voice activity detection (VAD), interruption handling, and turn coverage.
    // IMPORTANT: Example values shown here. Make sure to update for your use case.
    realtimeInputConfig: RealtimeInputConfig(
      automaticActivityDetection: ActivityDetectionConfig(
        startSensitivity: Sensitivity.low,
        endSensitivity: Sensitivity.low,
        prefixPaddingMS: 20,
        silenceDurationMS: 500,
      ),
      activityHandling: ActivityHandling.interrupt,
      turnCoverage: TurnCoverage.onlyActivity,
    ),
  ),
);

Unity 


// ...

var liveModel = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI()).GetLiveModel(
    modelName: "GEMINI_LIVE_API_MODEL_NAME",
    liveGenerationConfig: new LiveGenerationConfig(
        responseModalities: new[] { ResponseModality.Audio },
        // Configure voice activity detection (VAD), interruption handling, and turn coverage.
        // IMPORTANT: Example values shown here. Make sure to update for your use case.
        realtimeInputConfig: new RealtimeInputConfig(
            automaticActivityDetection: new ActivityDetectionConfig(
                startSensitivity: ActivityDetectionConfig.Sensitivity.Low,
                endSensitivity: ActivityDetectionConfig.Sensitivity.Low,
                prefixPaddingMS: 20,
                silenceDurationMS: 500
            ),
            activityHandling: RealtimeInputConfig.ActivityHandling.Interrupt,
            turnCoverage: RealtimeInputConfig.TurnCoverage.OnlyActivity
        )
    )
);

可用的 VAD 設定

設定 支援的值 說明
自動活動偵測 (automaticActivityDetection)
startSensitivity
  • LOW (預設)
  • HIGH

決定伺服器偵測使用者開始說話的靈敏度：

  • LOW：對微弱聲音較不敏感。這有助於避免環境噪音不小心觸發語音。
  • HIGH：更加靈敏。這有助於快速偵測較小聲的語音或輕聲細語。
endSensitivity
  • LOW (預設)
  • HIGH

決定伺服器偵測使用者停止說話的靈敏度：

  • LOW：對結尾停頓較不敏感。伺服器會容許句子結尾出現自然的猶豫或較小聲的字詞。
  • HIGH：更加靈敏。語音音量降低後，伺服器會立即結束語音對話。
prefixPadding 時間長度 (毫秒)
(預設：無 (0 毫秒))

定義偵測到語音之前要納入的音訊量。

這個「回溯」緩衝區可確保模型擷取完整的語音開頭，包括通常在偵測器觸發前就開始的第一個音節。

  • 0 的預設值可能會導致字詞開頭遭到裁剪。
  • 建議：20 至 50 毫秒
silenceDuration 時間長度 (毫秒)
(預設：約 800 毫秒)

定義伺服器在結束語音對話前，等待靜音的時間長度。這會決定系統對句子中間自然停頓 (例如思考、呼吸或子句邊界) 的容忍度。

  • 建議 (500 至 800 毫秒)： 提供良好的平衡，模型會收到完整且內容豐富的音訊，同時保持合理的回覆延遲時間。
  • 太低 (低於 200 毫秒)：在自然停頓時結束語音回合，將語句分割成小片段，可能會降低轉錄和回覆品質。
  • 過高 (超過 2000 毫秒)：模型開始回覆前，會出現明顯延遲。
中斷行為 (activityHandling)
activityHandling
  • INTERRUPT (預設)
  • NO_INTERRUPT

定義伺服器在生成回覆時，如何處理傳入的使用者活動：

  • INTERRUPT：偵測到使用者活動時，立即取消模型目前的回覆。
  • NO_INTERRUPT：繼續生成回覆，不中斷。
轉彎情境涵蓋率 (turnCoverage)
turnCoverage
  • ONLY_ACTIVITY (預設)
  • ALL_INPUT
  • AUDIO_ACTIVITY_AND_ALL_VIDEO

定義對話輪次情境中包含的串流輸入內容：

  • ONLY_ACTIVITY：排除無聲片段，只保留偵測到使用者活動的片段。
  • ALL_INPUT：保留所有串流輸入內容，包括無聲的音訊。
  • AUDIO_ACTIVITY_AND_ALL_VIDEO：保留所有串流影片影格，但只保留偵測到活動的音訊片段。

處理中斷

如果模型生成回覆時，伺服器偵測到使用者說話，且 activityHandling 設為 INTERRUPT (預設值)，請注意下列行為：

  • 取消生成：模型會立即停止回覆，並捨棄任何待處理的工具呼叫。

  • 工作階段記錄會遭到截斷：只有在服務中斷前已傳輸至應用程式的內容，才會保留在工作階段脈絡視窗中。

  • 發出中斷信號：伺服器傳送回應訊息，指出生成作業已中斷 (例如 Swift 中的 wasInterrupted，或 Kotlin、Java、Web、Flutter 和 Unity 中的 interrupted)。

停用自動語音活動偵測 (VAD)

如要完全手動控制對話輪次 (例如即按即說介面)，可以停用自動語音活動偵測 (VAD)，而非設定靈敏度參數。

停用自動偵測功能後，伺服器就不會自動偵測語音，也不會根據音訊靜音觸發回應。應用程式必須在活動工作階段期間，手動發出使用者活動邊界的信號。

1. 在模型設定中停用自動 VAD

按一下您的Gemini API供應商，即可在這個頁面查看供應商專屬內容和程式碼。

Swift 


// ...

let liveModel = FirebaseAI.firebaseAI(backend: .googleAI()).liveModel(
  modelName: "GEMINI_LIVE_API_MODEL_NAME",
  generationConfig: LiveGenerationConfig(
    responseModalities: [.audio],
    // Disable automatic voice activity detection (VAD).
    realtimeInputConfig: RealtimeInputConfig(
      automaticActivityDetection: .disabled()
    )
  )
)

Kotlin 


// ...

val liveModel = Firebase.ai(backend = GenerativeBackend.googleAI()).liveModel(
    modelName = "GEMINI_LIVE_API_MODEL_NAME",
    generationConfig = liveGenerationConfig {
        responseModality = ResponseModality.AUDIO
        // Disable automatic voice activity detection (VAD).
        realtimeInputConfig = realtimeInputConfig {
            automaticActivityDetection = ActivityDetectionConfig.disabled()
        }
    }
)

Java 


// ...

LiveGenerativeModel lm = FirebaseAI.getInstance(GenerativeBackend.googleAI()).liveModel(
        "GEMINI_LIVE_API_MODEL_NAME",
        new LiveGenerationConfig.Builder()
                .setResponseModality(ResponseModality.AUDIO)
                // Disable automatic voice activity detection (VAD).
                .setRealtimeInputConfig(RealtimeInputConfig.builder()
                        .setAutomaticActivityDetection(ActivityDetectionConfig.disabled())
                        .build())
                .build()
);

Web 

Not yet supported for Web apps - check back soon!

Dart 


// ...

final _liveModel = FirebaseAI.googleAI().liveGenerativeModel(
  model: 'GEMINI_LIVE_API_MODEL_NAME',
  liveGenerationConfig: LiveGenerationConfig(
    responseModalities: [ResponseModalities.audio],
    // Disable automatic voice activity detection (VAD).
    realtimeInputConfig: RealtimeInputConfig(
      automaticActivityDetection: ActivityDetectionConfig.disabled(),
    ),
  ),
);

Unity 


// ...

var liveModel = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI()).GetLiveModel(
    modelName: "GEMINI_LIVE_API_MODEL_NAME",
    liveGenerationConfig: new LiveGenerationConfig(
        responseModalities: new[] { ResponseModality.Audio },
        // Disable automatic voice activity detection (VAD).
        realtimeInputConfig: new RealtimeInputConfig(
            automaticActivityDetection: ActivityDetectionConfig.Disabled()
        )
    )
);

2. 手動表示使用者活動界線

如果停用 VAD，應用程式必須手動劃分每位使用者活動的回合界線：

  1. 信號活動開始：傳送音訊資料前，請先呼叫 sendStartActivityRealtime (例如使用者按下即按即說按鈕時)。

  2. 串流使用者輸入內容：使用 sendAudioRealtime 持續串流音訊 (或影片) 資料。

  3. 表示活動結束：使用者說完話時 (例如放開即按即說按鈕)，呼叫 sendStopActivityRealtime。這表示使用者已完成輸入，並觸發模型的回應。

Swift 

// If you disable automatic voice activity detection (VAD), you need to manually demarcate user activity.

// Signal the start of user activity (for example, on push-to-talk button press).
await session.sendStartActivityRealtime()

// Stream user audio data while the user speaks.
await session.sendAudioRealtime(audioData)

// Signal the end of user activity (for example, on button release) to trigger model response.
await session.sendStopActivityRealtime()

Kotlin 

// If you disable automatic voice activity detection (VAD), you need to manually demarcate user activity.

// Signal the start of user activity (for example, on push-to-talk button press).
session.sendStartActivityRealtime()

// Stream user audio data while the user speaks.
session.sendAudioRealtime(audioData)

// Signal the end of user activity (for example, on button release) to trigger model response.
session.sendStopActivityRealtime()

Java 

// If you disable automatic voice activity detection (VAD), you need to manually demarcate user activity.

// Signal the start of user activity (for example, on push-to-talk button press).
session.sendStartActivityRealtime();

// Stream user audio data while the user speaks.
session.sendAudioRealtime(audioData);

// Signal the end of user activity (for example, on button release) to trigger model response.
session.sendStopActivityRealtime();

Web 

Not yet supported for Web apps - check back soon!

Dart 

// If you disable automatic voice activity detection (VAD), you need to manually demarcate user activity.

// Signal the start of user activity (for example, on push-to-talk button press).
await session.sendStartActivityRealtime();

// Stream user audio data while the user speaks.
await session.sendAudioRealtime(audioData);

// Signal the end of user activity (for example, on button release) to trigger model response.
await session.sendStopActivityRealtime();

Unity 

// If you disable automatic voice activity detection (VAD), you need to manually demarcate user activity.

// Signal the start of user activity (for example, on push-to-talk button press).
await session.SendStartActivityRealtimeAsync();

// Stream user audio data while the user speaks.
await session.SendAudioRealtimeAsync(audio: audioData);

// Signal the end of user activity (for example, on button release) to trigger model response.
await session.SendStopActivityRealtimeAsync();


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