Quickstart: Using client libraries

This page shows you how to send a speech recognition request to Speech-to-Text in your favorite programming language using the Google Cloud Client Libraries.

Speech-to-Text enables easy integration of Google speech recognition technologies into developer applications. You can send audio data to the Speech-to-Text API, which then returns a text transcription of that audio file. For more information about the service, see Speech-to-Text basics.

Before you begin

Before you can send a request to the Speech-to-Text API, you must have completed the following actions. See the before you begin page for details.

  • Enable Speech-to-Text on a GCP project.
    1. Make sure billing is enabled for Speech-to-Text.
    2. Create and/or assign one or more service accounts to Speech-to-Text.
    3. Download a service account credential key.
  • Set your authentication environment variable.
  • (Optional) Create a new Google Cloud Storage bucket to store your audio data.

Install the client library

Go

go get -u cloud.google.com/go/speech/apiv1

Java

If you are using Maven, add the following to your pom.xml file. For more information about BOMs, see The Google Cloud Platform Libraries BOM.

<dependencyManagement>
  <dependencies>
    <dependency>
      <groupId>com.google.cloud</groupId>
      <artifactId>libraries-bom</artifactId>
      <version>23.0.0</version>
      <type>pom</type>
      <scope>import</scope>
    </dependency>
  </dependencies>
</dependencyManagement>

<dependencies>
  <dependency>
    <groupId>com.google.cloud</groupId>
    <artifactId>google-cloud-speech</artifactId>
  </dependency>
</dependencies>

If you are using Gradle, add the following to your dependencies:

implementation platform('com.google.cloud:libraries-bom:23.0.0')

implementation 'com.google.cloud:google-cloud-speech'

If you are using sbt, add the following to your dependencies:

libraryDependencies += "com.google.cloud" % "google-cloud-speech" % "2.0.4"

If you're using Visual Studio Code, IntelliJ, or Eclipse, you can add client libraries to your project using the following IDE plugins:

The plugins provide additional functionality, such as key management for service accounts. Refer to each plugin's documentation for details.

Node.js

Before installing the library, make sure you've prepared your environment for Node.js development.

npm install --save @google-cloud/speech

Python

Before installing the library, make sure you've prepared your environment for Python development.

pip install --upgrade google-cloud-speech

Make an audio transcription request

Now you can use Speech-to-Text to transcribe an audio file to text. Use the following code to send a recognize request to the Speech-to-Text API.

Go


// Sample speech-quickstart uses the Google Cloud Speech API to transcribe
// audio.
package main

import (
	"context"
	"fmt"
	"log"

	speech "cloud.google.com/go/speech/apiv1"
	speechpb "google.golang.org/genproto/googleapis/cloud/speech/v1"
)

func main() {
	ctx := context.Background()

	// Creates a client.
	client, err := speech.NewClient(ctx)
	if err != nil {
		log.Fatalf("Failed to create client: %v", err)
	}
	defer client.Close()

	// The path to the remote audio file to transcribe.
	fileURI := "gs://cloud-samples-data/speech/brooklyn_bridge.raw"

	// Detects speech in the audio file.
	resp, err := client.Recognize(ctx, &speechpb.RecognizeRequest{
		Config: &speechpb.RecognitionConfig{
			Encoding:        speechpb.RecognitionConfig_LINEAR16,
			SampleRateHertz: 16000,
			LanguageCode:    "en-US",
		},
		Audio: &speechpb.RecognitionAudio{
			AudioSource: &speechpb.RecognitionAudio_Uri{Uri: fileURI},
		},
	})
	if err != nil {
		log.Fatalf("failed to recognize: %v", err)
	}

	// Prints the results.
	for _, result := range resp.Results {
		for _, alt := range result.Alternatives {
			fmt.Printf("\"%v\" (confidence=%3f)\n", alt.Transcript, alt.Confidence)
		}
	}
}

Java

samples/snippets/src/main/java/com/example/speech/QuickstartSample.java 
// Imports the Google Cloud client library
import com.google.cloud.speech.v1.RecognitionAudio;
import com.google.cloud.speech.v1.RecognitionConfig;
import com.google.cloud.speech.v1.RecognitionConfig.AudioEncoding;
import com.google.cloud.speech.v1.RecognizeResponse;
import com.google.cloud.speech.v1.SpeechClient;
import com.google.cloud.speech.v1.SpeechRecognitionAlternative;
import com.google.cloud.speech.v1.SpeechRecognitionResult;
import java.util.List;

public class QuickstartSample {

  /** Demonstrates using the Speech API to transcribe an audio file. */
  public static void main(String... args) throws Exception {
    // Instantiates a client
    try (SpeechClient speechClient = SpeechClient.create()) {

      // The path to the audio file to transcribe
      String gcsUri = "gs://cloud-samples-data/speech/brooklyn_bridge.raw";

      // Builds the sync recognize request
      RecognitionConfig config =
          RecognitionConfig.newBuilder()
              .setEncoding(AudioEncoding.LINEAR16)
              .setSampleRateHertz(16000)
              .setLanguageCode("en-US")
              .build();
      RecognitionAudio audio = RecognitionAudio.newBuilder().setUri(gcsUri).build();

      // Performs speech recognition on the audio file
      RecognizeResponse response = speechClient.recognize(config, audio);
      List<SpeechRecognitionResult> results = response.getResultsList();

      for (SpeechRecognitionResult result : results) {
        // There can be several alternative transcripts for a given chunk of speech. Just use the
        // first (most likely) one here.
        SpeechRecognitionAlternative alternative = result.getAlternativesList().get(0);
        System.out.printf("Transcription: %s%n", alternative.getTranscript());
      }
    }
  }
}

Node.js

Before running the example, make sure you've prepared your environment for Node.js development.

// Imports the Google Cloud client library
const speech = require('@google-cloud/speech');

// Creates a client
const client = new speech.SpeechClient();

async function quickstart() {
  // The path to the remote LINEAR16 file
  const gcsUri = 'gs://cloud-samples-data/speech/brooklyn_bridge.raw';

  // The audio file's encoding, sample rate in hertz, and BCP-47 language code
  const audio = {
    uri: gcsUri,
  };
  const config = {
    encoding: 'LINEAR16',
    sampleRateHertz: 16000,
    languageCode: 'en-US',
  };
  const request = {
    audio: audio,
    config: config,
  };

  // Detects speech in the audio file
  const [response] = await client.recognize(request);
  const transcription = response.results
    .map(result => result.alternatives[0].transcript)
    .join('\n');
  console.log(`Transcription: ${transcription}`);
}
quickstart();

Python

Before running the example, make sure you've prepared your environment for Python development.

samples/snippets/quickstart.py 

# Imports the Google Cloud client library
from google.cloud import speech


# Instantiates a client
client = speech.SpeechClient()

# The name of the audio file to transcribe
gcs_uri = "gs://cloud-samples-data/speech/brooklyn_bridge.raw"

audio = speech.RecognitionAudio(uri=gcs_uri)

config = speech.RecognitionConfig(
    encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
    sample_rate_hertz=16000,
    language_code="en-US",
)

# Detects speech in the audio file
response = client.recognize(config=config, audio=audio)

for result in response.results:
    print("Transcript: {}".format(result.alternatives[0].transcript))

Congratulations! You've sent your first request to Speech-to-Text.

If you receive an error or an empty response from Speech-to-Text, take a look at the troubleshooting and error mitigation steps.

Clean up

To avoid incurring charges to your Google Cloud account for the resources used in this page, follow these steps.

  • Use the Cloud Console to delete your project if you do not need it.

What's next