Transcrever voz em texto usando as bibliotecas de cliente

Esta página mostra como enviar uma solicitação de reconhecimento de fala para o Speech-to-Text em sua linguagem de programação favorita usando as bibliotecas de cliente do Google Cloud.

A Speech-to-Text permite a fácil integração das tecnologias de reconhecimento de fala do Google nos aplicativos do desenvolvedor. Você pode enviar dados de áudio para a API Speech-to-Text, que em seguida retorna uma transcrição de texto desse arquivo de áudio. Para mais informações sobre o serviço, consulte Princípios básicos da Speech-to-Text.

Antes de começar

Antes de enviar uma solicitação para a API Speech-to-Text, é necessário concluir as ações a seguir. Consulte a página antes de começar para ver os detalhes.

  • Ativar o Speech-to-Text em um projeto do Google Cloud.
  • Verificar se o faturamento está ativado para o Speech-to-Text.

  • After installing the Google Cloud CLI, initialize it by running the following command: 

    gcloud init

    If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

  • If you're using a local shell, then create local authentication credentials for your user account: 

    gcloud auth application-default login

    You don't need to do this if you're using Cloud Shell.

    If an authentication error is returned, confirm that you have configured the gcloud CLI to use Workforce Identity Federation.

  • (Opcional) Criar um novo bucket do Google Cloud Storage para armazenar dados de áudio.

Instale a biblioteca de cliente

Go

go get 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>26.56.0</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 'com.google.cloud:google-cloud-speech:4.54.0'

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

libraryDependencies += "com.google.cloud" % "google-cloud-speech" % "4.54.0"

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

Antes de instalar a biblioteca, verifique se você preparou seu ambiente para o desenvolvimento do Node.js.

npm install --save @google-cloud/speech

Python

Antes de instalar a biblioteca, verifique se você preparou seu ambiente para o desenvolvimento do Python.

pip install --upgrade google-cloud-speech

Fazer uma solicitação de transcrição de áudio

Use o Speech-to-Text para transcrever um arquivo de áudio para texto. Use o código a seguir para enviar uma solicitação recognize para a API Speech-to-Text.

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"
	"cloud.google.com/go/speech/apiv1/speechpb"
)

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

// 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

Antes de executar o exemplo, verifique se você preparou o ambiente para o desenvolvimento em Node.js.

// 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

Antes de executar o exemplo, verifique se você preparou o ambiente para o desenvolvimento em Python.


# Imports the Google Cloud client library


from google.cloud import speech



def run_quickstart() -> speech.RecognizeResponse:
    # 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(f"Transcript: {result.alternatives[0].transcript}")

Parabéns! Você enviou sua primeira solicitação para o Speech-to-Text.

Se você receber um erro ou uma resposta vazia do Speech to Text, analise as etapas de solução de problemas e de eliminação de erros.

Limpar

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