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

  1. Sign in to your Google Account.

    If you don't already have one, sign up for a new account.

  2. Set up a Cloud Console project.

    Set up a project

    Click to:

    • Create or select a project.
    • Enable the Cloud Speech-to-Text API for that project.
    • Create a service account.
    • Download a private key as JSON.

    You can view and manage these resources at any time in the Cloud Console.

  3. Set the environment variable GOOGLE_APPLICATION_CREDENTIALS to the path of the JSON file that contains your service account key. This variable only applies to your current shell session, so if you open a new session, set the variable again.

  4. Install and initialize the Cloud SDK.

Install the client library

C#

Install-Package Google.Cloud.Speech.V1 -Pre

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>5.3.0</version>
      <type>pom</type>
      <scope>import</scope>
    </dependency>
  </dependencies>
</dependencyManagement>

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

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

compile 'com.google.cloud:google-cloud-speech:1.23.0'

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

libraryDependencies += "com.google.cloud" % "google-cloud-speech" % "1.23.0"

If you're using 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

PHP

composer require google/cloud-speech

Python

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

pip install --upgrade google-cloud-speech

Ruby

gem install 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.

C#


using Google.Cloud.Speech.V1;
using System;

namespace GoogleCloudSamples
{
    public class QuickStart
    {
        // The name of the local audio file to transcribe
        public static string DEMO_FILE = "audio.raw";
        public static void Main(string[] args)
        {
            var speech = SpeechClient.Create();
            var response = speech.Recognize(new RecognitionConfig()
            {
                Encoding = RecognitionConfig.Types.AudioEncoding.Linear16,
                SampleRateHertz = 16000,
                LanguageCode = "en",
            }, RecognitionAudio.FromFile(DEMO_FILE));
            foreach (var result in response.Results)
            {
                foreach (var alternative in result.Alternatives)
                {
                    Console.WriteLine(alternative.Transcript);
                }
            }
        }
    }
}

Go


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

import (
	"context"
	"fmt"
	"io/ioutil"
	"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)
	}

	// Sets the name of the audio file to transcribe.
	filename := "/path/to/audio.raw"

	// Reads the audio file into memory.
	data, err := ioutil.ReadFile(filename)
	if err != nil {
		log.Fatalf("Failed to read file: %v", err)
	}

	// 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_Content{Content: data},
		},
	})
	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

// 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 com.google.protobuf.ByteString;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
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 fileName = "./resources/audio.raw";

      // Reads the audio file into memory
      Path path = Paths.get(fileName);
      byte[] data = Files.readAllBytes(path);
      ByteString audioBytes = ByteString.copyFrom(data);

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

async function main() {
  // Imports the Google Cloud client library
  const speech = require('@google-cloud/speech');
  const fs = require('fs');

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

  // The name of the audio file to transcribe
  const fileName = './resources/audio.raw';

  // Reads a local audio file and converts it to base64
  const file = fs.readFileSync(fileName);
  const audioBytes = file.toString('base64');

  // The audio file's encoding, sample rate in hertz, and BCP-47 language code
  const audio = {
    content: audioBytes,
  };
  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}`);
}
main().catch(console.error);

PHP

# Includes the autoloader for libraries installed with composer
require __DIR__ . '/vendor/autoload.php';

# Imports the Google Cloud client library
use Google\Cloud\Speech\V1\SpeechClient;
use Google\Cloud\Speech\V1\RecognitionAudio;
use Google\Cloud\Speech\V1\RecognitionConfig;
use Google\Cloud\Speech\V1\RecognitionConfig\AudioEncoding;

# The name of the audio file to transcribe
$audioFile = __DIR__ . '/test/data/audio32KHz.raw';

# get contents of a file into a string
$content = file_get_contents($audioFile);

# set string as audio content
$audio = (new RecognitionAudio())
    ->setContent($content);

# The audio file's encoding, sample rate and language
$config = new RecognitionConfig([
    'encoding' => AudioEncoding::LINEAR16,
    'sample_rate_hertz' => 32000,
    'language_code' => 'en-US'
]);

# Instantiates a client
$client = new SpeechClient();

# Detects speech in the audio file
$response = $client->recognize($config, $audio);

# Print most likely transcription
foreach ($response->getResults() as $result) {
    $alternatives = $result->getAlternatives();
    $mostLikely = $alternatives[0];
    $transcript = $mostLikely->getTranscript();
    printf('Transcript: %s' . PHP_EOL, $transcript);
}

$client->close();

Python

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

from google.cloud import speech_v1p1beta1
from google.cloud.speech_v1p1beta1 import enums


def sample_recognize(storage_uri):
    """
    Performs synchronous speech recognition on an audio file

    Args:
      storage_uri URI for audio file in Cloud Storage, e.g. gs://[BUCKET]/[FILE]
    """

    client = speech_v1p1beta1.SpeechClient()

    # storage_uri = 'gs://cloud-samples-data/speech/brooklyn_bridge.mp3'

    # The language of the supplied audio
    language_code = "en-US"

    # Sample rate in Hertz of the audio data sent
    sample_rate_hertz = 44100

    # Encoding of audio data sent. This sample sets this explicitly.
    # This field is optional for FLAC and WAV audio formats.
    encoding = enums.RecognitionConfig.AudioEncoding.MP3
    config = {
        "language_code": language_code,
        "sample_rate_hertz": sample_rate_hertz,
        "encoding": encoding,
    }
    audio = {"uri": storage_uri}

    response = client.recognize(config, audio)
    for result in response.results:
        # First alternative is the most probable result
        alternative = result.alternatives[0]
        print(u"Transcript: {}".format(alternative.transcript))

Ruby

# Imports the Google Cloud client library
require "google/cloud/speech"

# Instantiates a client
speech = Google::Cloud::Speech.speech

# The name of the audio file to transcribe
file_name = "./resources/brooklyn_bridge.raw"

# The raw audio
audio_file = File.binread file_name

# The audio file's encoding and sample rate
config = { encoding:          :LINEAR16,
           sample_rate_hertz: 16_000,
           language_code:     "en-US" }
audio  = { content: audio_file }

# Detects speech in the audio file
response = speech.recognize config: config, audio: audio

results = response.results

# Get first result because we only processed a single audio file
# Each result represents a consecutive portion of the audio
results.first.alternatives.each do |alternatives|
  puts "Transcription: #{alternatives.transcript}"
end

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 quickstart, follow these steps.

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

What's next