Detect intent with audio output

Applications often need a bot to talk back to the end-user. Dialogflow Applications often need a bot to talk back to the end user. Dialogflow lets you use Cloud Text-to-Speech powered by DeepMind WaveNet to generate speech responses from your agent. This conversion from intent text responses to audio is called audio output, speech synthesis,

You can use audio for both input and output when detecting an intent. This is common when developing apps that communicate with users using a purely audio interface.

For a list of supported languages, see the TTS column on the Languages page.

Before you begin

This feature is only applicable when using the API for end-user interactions. If you are using an integration, you can skip this guide.

Before you begin, complete the following steps:

• Read Dialogflow basics.
• Perform setup steps.

Create an agent

1. Go to the Dialogflow ES console.
2. Sign in to the console if prompted. For more information, see the Dialogflow console overview.
3. In the sidebar menu, expand Loading agents.
4. Click Create new agent.
5. Enter the agent name, default language, and default time zone.
6. Enter an existing project. To let the Dialogflow console create a project, select Create a new Google project.
7. Click Create.

Detect intent

To detect intent, call the detectIntent method on the Sessions type.

REST

1. Prepare audio content

Download the book-a-room.wav sample input_audio file, which says "book a room." The audio file must be base64-encoded for this example, so it can be provided in the JSON request below.

Here is a Linux example:

wget https://cloud.google.com/dialogflow/es/docs/data/book-a-room.wav
base64 -w 0 book-a-room.wav > book-a-room.b64

For examples on other platforms, see Embedding Base64-encoded audio in the Cloud Speech API documentation.

2. Make detect intent request

Call the detectIntent method on the Sessions type and specify base64-encoded audio.

Before using any of the request data, make the following replacements:

• PROJECT_ID: your Google Cloud project ID
• SESSION_ID: a session ID
• BASE64_AUDIO: the base64 content from the output file above

HTTP method and URL:

POST https://dialogflow.googleapis.com/v2/projects/PROJECT_ID/agent/sessions/SESSION_ID:detectIntent

Request JSON body:

{
  "queryInput": {
    "audioConfig": {
      "languageCode": "en-US"
    }
  },
  "outputAudioConfig" : {
    "audioEncoding": "OUTPUT_AUDIO_ENCODING_LINEAR_16"
  },
  "inputAudio": "BASE64_AUDIO"
}

To send your request, expand one of these options:

curl (Linux, macOS, or Cloud Shell)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell, which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "x-goog-user-project: PROJECT_ID" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://dialogflow.googleapis.com/v2/projects/PROJECT_ID/agent/sessions/SESSION_ID:detectIntent"

PowerShell (Windows)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "PROJECT_ID" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://dialogflow.googleapis.com/v2/projects/PROJECT_ID/agent/sessions/SESSION_ID:detectIntent" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "responseId": "b7405848-2a3a-4e26-b9c6-c4cf9c9a22ee",
  "queryResult": {
    "queryText": "book a room",
    "speechRecognitionConfidence": 0.8616504,
    "action": "room.reservation",
    "parameters": {
      "time": "",
      "date": "",
      "duration": "",
      "guests": "",
      "location": ""
    },
    "fulfillmentText": "I can help with that. Where would you like to reserve a room?",
    "fulfillmentMessages": [
      {
        "text": {
          "text": [
            "I can help with that. Where would you like to reserve a room?"
          ]
        }
      }
    ],
    "intent": {
      "name": "projects/PROJECT_ID/agent/intents/e8f6a63e-73da-4a1a-8bfc-857183f71228",
      "displayName": "room.reservation"
    },
    "intentDetectionConfidence": 1,
    "diagnosticInfo": {},
    "languageCode": "en-us"
  },
  "outputAudio": "UklGRs6vAgBXQVZFZm10IBAAAAABAAEAwF0AAIC7AA..."
}

Notice that the value of the queryResult.action field is room.reservation and the outputAudio field contains a large base64 audio string.

3. Play output audio

Copy the text from the outputAudio field and save it in a file named output_audio.b64. This file needs to be converted to audio.

Here is a Linux example:

base64 -d output_audio.b64 > output_audio.wav

For examples on other platforms, see Decoding Base64-Encoded Audio Content in the text-to-speech API documentation.

You can now play the output_audio.wav audio file and hear that it matches the text from the queryResult.fulfillmentMessages[1].text.text[0] field above. The second fulfillmentMessages element is chosen because it's the text response for the default platform.

Java

To authenticate to Dialogflow CX, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

import com.google.api.gax.rpc.ApiException;
import com.google.cloud.dialogflow.v2.DetectIntentRequest;
import com.google.cloud.dialogflow.v2.DetectIntentResponse;
import com.google.cloud.dialogflow.v2.OutputAudioConfig;
import com.google.cloud.dialogflow.v2.OutputAudioEncoding;
import com.google.cloud.dialogflow.v2.QueryInput;
import com.google.cloud.dialogflow.v2.QueryResult;
import com.google.cloud.dialogflow.v2.SessionName;
import com.google.cloud.dialogflow.v2.SessionsClient;
import com.google.cloud.dialogflow.v2.TextInput;
import com.google.common.collect.Maps;
import java.io.IOException;
import java.util.List;
import java.util.Map;

public class DetectIntentWithTextToSpeechResponse {

  public static Map<String, QueryResult> detectIntentWithTexttoSpeech(
      String projectId, List<String> texts, String sessionId, String languageCode)
      throws IOException, ApiException {
    Map<String, QueryResult> queryResults = Maps.newHashMap();
    // Instantiates a client
    try (SessionsClient sessionsClient = SessionsClient.create()) {
      // Set the session name using the sessionId (UUID) and projectID (my-project-id)
      SessionName session = SessionName.of(projectId, sessionId);
      System.out.println("Session Path: " + session.toString());

      // Detect intents for each text input
      for (String text : texts) {
        // Set the text (hello) and language code (en-US) for the query
        TextInput.Builder textInput =
            TextInput.newBuilder().setText(text).setLanguageCode(languageCode);

        // Build the query with the TextInput
        QueryInput queryInput = QueryInput.newBuilder().setText(textInput).build();

        //
        OutputAudioEncoding audioEncoding = OutputAudioEncoding.OUTPUT_AUDIO_ENCODING_LINEAR_16;
        int sampleRateHertz = 16000;
        OutputAudioConfig outputAudioConfig =
            OutputAudioConfig.newBuilder()
                .setAudioEncoding(audioEncoding)
                .setSampleRateHertz(sampleRateHertz)
                .build();

        DetectIntentRequest dr =
            DetectIntentRequest.newBuilder()
                .setQueryInput(queryInput)
                .setOutputAudioConfig(outputAudioConfig)
                .setSession(session.toString())
                .build();

        // Performs the detect intent request
        DetectIntentResponse response = sessionsClient.detectIntent(dr);

        // Display the query result
        QueryResult queryResult = response.getQueryResult();

        System.out.println("====================");
        System.out.format("Query Text: '%s'\n", queryResult.getQueryText());
        System.out.format(
            "Detected Intent: %s (confidence: %f)\n",
            queryResult.getIntent().getDisplayName(), queryResult.getIntentDetectionConfidence());
        System.out.format(
            "Fulfillment Text: '%s'\n",
            queryResult.getFulfillmentMessagesCount() > 0
                ? queryResult.getFulfillmentMessages(0).getText()
                : "Triggered Default Fallback Intent");

        queryResults.put(text, queryResult);
      }
    }
    return queryResults;
  }
}

Node.js

To authenticate to Dialogflow CX, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

// Imports the Dialogflow client library
const dialogflow = require('@google-cloud/dialogflow').v2;

// Instantiate a DialogFlow client.
const sessionClient = new dialogflow.SessionsClient();

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const projectId = 'ID of GCP project associated with your Dialogflow agent';
// const sessionId = `user specific ID of session, e.g. 12345`;
// const query = `phrase(s) to pass to detect, e.g. I'd like to reserve a room for six people`;
// const languageCode = 'BCP-47 language code, e.g. en-US';
// const outputFile = `path for audio output file, e.g. ./resources/myOutput.wav`;

// Define session path
const sessionPath = sessionClient.projectAgentSessionPath(
  projectId,
  sessionId
);
const fs = require('fs');
const util = require('util');

async function detectIntentwithTTSResponse() {
  // The audio query request
  const request = {
    session: sessionPath,
    queryInput: {
      text: {
        text: query,
        languageCode: languageCode,
      },
    },
    outputAudioConfig: {
      audioEncoding: 'OUTPUT_AUDIO_ENCODING_LINEAR_16',
    },
  };
  sessionClient.detectIntent(request).then(responses => {
    console.log('Detected intent:');
    const audioFile = responses[0].outputAudio;
    util.promisify(fs.writeFile)(outputFile, audioFile, 'binary');
    console.log(`Audio content written to file: ${outputFile}`);
  });
}
detectIntentwithTTSResponse();

Python

To authenticate to Dialogflow CX, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

def detect_intent_with_texttospeech_response(
    project_id, session_id, texts, language_code
):
    """Returns the result of detect intent with texts as inputs and includes
    the response in an audio format.

    Using the same `session_id` between requests allows continuation
    of the conversation."""
    from google.cloud import dialogflow

    session_client = dialogflow.SessionsClient()

    session_path = session_client.session_path(project_id, session_id)
    print("Session path: {}\n".format(session_path))

    for text in texts:
        text_input = dialogflow.TextInput(text=text, language_code=language_code)

        query_input = dialogflow.QueryInput(text=text_input)

        # Set the query parameters with sentiment analysis
        output_audio_config = dialogflow.OutputAudioConfig(
            audio_encoding=dialogflow.OutputAudioEncoding.OUTPUT_AUDIO_ENCODING_LINEAR_16
        )

        request = dialogflow.DetectIntentRequest(
            session=session_path,
            query_input=query_input,
            output_audio_config=output_audio_config,
        )
        response = session_client.detect_intent(request=request)

        print("=" * 20)
        print("Query text: {}".format(response.query_result.query_text))
        print(
            "Detected intent: {} (confidence: {})\n".format(
                response.query_result.intent.display_name,
                response.query_result.intent_detection_confidence,
            )
        )
        print("Fulfillment text: {}\n".format(response.query_result.fulfillment_text))
        # The response's audio_content is binary.
        with open("output.wav", "wb") as out:
            out.write(response.output_audio)
            print('Audio content written to file "output.wav"')

For more information about the relevant response fields, see the Detect intent responses section.

Detect intent responses

The response for a detect intent request is a DetectIntentResponse type.

Normal detect intent processing controls the content of the DetectIntentResponse.queryResult.fulfillmentMessages field.

The DetectIntentResponse.outputAudio field is populated with audio based on the values of default platform text responses found in the DetectIntentResponse.queryResult.fulfillmentMessages field:

• If multiple default text responses exist, they are concatenated when generating audio.
• If no default platform text responses exist, the generated audio content is empty.

The DetectIntentResponse.outputAudioConfig field is populated with audio settings used to generate the output audio.

Detect intent from a stream

When detecting intent from a stream, you send requests similar to the example that does not use output audio: Detecting Intent from a Stream. However, you supply an OutputAudioConfig field to the request. The output_audio and output_audio_config fields are populated in the final streaming response that you get from the Dialogflow API server. For more information, see StreamingDetectIntentRequest and StreamingDetectIntentResponse.

Agent settings for speech

You can control various aspects of speech synthesis. See the Agent speech settings.

Note: API calls that provide output audio config override all existing text-to-speech settings applied to the agent.

Use the Dialogflow simulator

You can interact with the agent and receive audio responses using the Dialogflow simulator:

1. Enable automatic text-to-speech by following the instructions in Agent speech settings.
2. Type or say "book a room" in the simulator.
3. View the output audio section in the simulator.