긴 오디오 파일 스크립트 작성

이 페이지는 비동기 음성 인식을 사용하여 긴 오디오 파일(1분 이상)을 텍스트로 변환하는 방법을 설명합니다.

비동기 음성 인식은 장기 실행 오디오 처리 작업을 시작합니다. 비동기 음성 인식을 사용하여 1분 이상의 오디오를 인식할 수 있습니다. 이보다 짧은 오디오는 동기 음성 인식으로 더 빠르고 단순하게 처리할 수 있습니다.

google.longrunning.Operations 인터페이스를 통해 작업 결과를 검색할 수 있습니다. 결과는 5일(120시간) 동안 검색할 수 있습니다. 오디오 콘텐츠를 Speech-to-Text에 직접 보내거나 Speech-to-Text가 Google Cloud Storage에 있는 기존 오디오 콘텐츠를 처리할 수 있습니다. 비동기식 음성 인식 요청에 대한 오디오 제한도 참조하세요.

Google Cloud Storage 파일을 사용하여 긴 오디오 파일 텍스트 변환

이 샘플은 Cloud Storage 버킷을 사용하여 장기 실행 텍스트 변환 프로세스의 원시 오디오 입력을 저장합니다.

프로토콜

자세한 내용은 speech:longrunningrecognize API 엔드포인트를 참조하세요.

동기 음성 인식을 수행하려면 POST 요청을 하고 적절한 요청 본문을 제공합니다. 다음은 curl을 사용한 POST 요청의 예시입니다. 이 예시에서는 Google Cloud Cloud SDK를 사용하는 프로젝트용으로 설정된 서비스 계정의 액세스 토큰을 사용합니다. Cloud SDK 설치, 서비스 계정으로 프로젝트 설정, 액세스 토큰 획득 방법은 빠른 시작을 참조하세요.

curl -X POST \
     -H "Authorization: Bearer "$(gcloud auth application-default print-access-token) \
     -H "Content-Type: application/json; charset=utf-8" \
     --data "{
  'config': {
    'language_code': 'en-US'
  },
  'audio':{
    'uri':'gs://gcs-test-data/vr.flac'
  }
}" "https://speech.googleapis.com/v1/speech:longrunningrecognize"

요청 본문 구성에 대한 자세한 내용은 RecognitionConfigRecognitionAudio 참조 문서를 확인하세요.

요청이 성공하면 서버가 200 OK HTTP 상태 코드와 응답을 JSON 형식으로 반환합니다.

{
  "name": "7612202767953098924"
}

여기서 name는 요청에 대해 생성된 장기 실행 작업 이름입니다.

처리가 완료될 때까지 기다립니다. 처리 시간은 소스 오디오에 따라 다르며, 대부분의 경우에는 소스 오디오 길이의 절반으로 표시됩니다. 장기 실행 작업의 상태는 https://speech.googleapis.com/v1/operations/ 엔드포인트에 GET 요청을 실행하여 알아볼 수 있습니다. your-operation-namelongrunningrecognize 요청으로부터 반환된 name으로 대체합니다. 요청의 예상 진행률은 progressPercent 입력란을 통해 알 수 있습니다.

curl -H "Authorization: Bearer "$(gcloud auth application-default print-access-token) \
     -H "Content-Type: application/json; charset=utf-8" \
     "https://speech.googleapis.com/v1/operations/your-operation-name"

요청이 성공하면 서버가 200 OK HTTP 상태 코드와 응답을 JSON 형식으로 반환합니다.

{
  "name": "7612202767953098924",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.speech.v1.LongRunningRecognizeMetadata",
    "progressPercent": 100,
    "startTime": "2017-07-20T16:36:55.033650Z",
    "lastUpdateTime": "2017-07-20T16:37:17.158630Z"
  },
  "done": true,
  "response": {
    "@type": "type.googleapis.com/google.cloud.speech.v1.LongRunningRecognizeResponse",
    "results": [
      {
        "alternatives": [
          {
            "transcript": "okay so what am I doing here...(etc)...",
            "confidence": 0.96096134,
          }
        ]
      },
      {
        "alternatives": [
          {
            ...
          }
        ]
      }
    ]
  }
}

작업이 완료되지 않았으면 응답의 done 속성이 true가 될 때까지 GET 요청을 반복해서 엔드포인트를 폴링할 수 있습니다.

gcloud 명령어

자세한 내용은 recognize-long-running 명령어를 참조하세요.

비동기 음성 인식을 수행하려면 gcloud 명령줄 도구를 사용하여 로컬 파일 또는 Google Cloud Storage URL의 경로를 제공합니다.

gcloud ml speech recognize-long-running \
    'gs://cloud-samples-tests/speech/brooklyn.flac' \
     --language-code='en-US' --async

요청이 성공하면 서버가 장기 실행 작업의 ID를 JSON 형식으로 반환합니다.

{
  "name": OPERATION_ID
}

그런 다음 다음 명령어를 실행하여 작업에 대한 정보를 얻을 수 있습니다.

gcloud ml speech operations describe OPERATION_ID

또한 다음 명령어를 실행하여 작업이 완료될 때까지 작업을 폴링할 수 있습니다.

gcloud ml speech operations wait OPERATION_ID

작업이 완료되면 오디오 스크립트가 JSON 형식으로 반환됩니다.

{
  "@type": "type.googleapis.com/google.cloud.speech.v1.LongRunningRecognizeResponse",
  "results": [
    {
      "alternatives": [
        {
          "confidence": 0.9840146,
          "transcript": "how old is the Brooklyn Bridge"
        }
      ]
    }
  ]
}

C#

static object AsyncRecognizeGcs(string storageUri)
{
    var speech = SpeechClient.Create();
    var longOperation = speech.LongRunningRecognize(new RecognitionConfig()
    {
        Encoding = RecognitionConfig.Types.AudioEncoding.Linear16,
        SampleRateHertz = 16000,
        LanguageCode = "en",
    }, RecognitionAudio.FromStorageUri(storageUri));
    longOperation = longOperation.PollUntilCompleted();
    var response = longOperation.Result;
    foreach (var result in response.Results)
    {
        foreach (var alternative in result.Alternatives)
        {
            Console.WriteLine($"Transcript: { alternative.Transcript}");
        }
    }
    return 0;
}

Go


func sendGCS(w io.Writer, client *speech.Client, gcsURI string) error {
	ctx := context.Background()

	// Send the contents of the audio file with the encoding and
	// and sample rate information to be transcripted.
	req := &speechpb.LongRunningRecognizeRequest{
		Config: &speechpb.RecognitionConfig{
			Encoding:        speechpb.RecognitionConfig_LINEAR16,
			SampleRateHertz: 16000,
			LanguageCode:    "en-US",
		},
		Audio: &speechpb.RecognitionAudio{
			AudioSource: &speechpb.RecognitionAudio_Uri{Uri: gcsURI},
		},
	}

	op, err := client.LongRunningRecognize(ctx, req)
	if err != nil {
		return err
	}
	resp, err := op.Wait(ctx)
	if err != nil {
		return err
	}

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

자바

/**
 * Performs non-blocking speech recognition on remote FLAC file and prints the transcription.
 *
 * @param gcsUri the path to the remote LINEAR16 audio file to transcribe.
 */
public static void asyncRecognizeGcs(String gcsUri) throws Exception {
  // Instantiates a client with GOOGLE_APPLICATION_CREDENTIALS
  try (SpeechClient speech = SpeechClient.create()) {

    // Configure remote file request for FLAC
    RecognitionConfig config =
        RecognitionConfig.newBuilder()
            .setEncoding(AudioEncoding.FLAC)
            .setLanguageCode("en-US")
            .setSampleRateHertz(16000)
            .build();
    RecognitionAudio audio = RecognitionAudio.newBuilder().setUri(gcsUri).build();

    // Use non-blocking call for getting file transcription
    OperationFuture<LongRunningRecognizeResponse, LongRunningRecognizeMetadata> response =
        speech.longRunningRecognizeAsync(config, audio);
    while (!response.isDone()) {
      System.out.println("Waiting for response...");
      Thread.sleep(10000);
    }

    List<SpeechRecognitionResult> results = response.get().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

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

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

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const gcsUri = 'gs://my-bucket/audio.raw';
// const encoding = 'Encoding of the audio file, e.g. LINEAR16';
// const sampleRateHertz = 16000;
// const languageCode = 'BCP-47 language code, e.g. en-US';

const config = {
  encoding: encoding,
  sampleRateHertz: sampleRateHertz,
  languageCode: languageCode,
};

const audio = {
  uri: gcsUri,
};

const request = {
  config: config,
  audio: audio,
};

// Detects speech in the audio file. This creates a recognition job that you
// can wait for now, or get its result later.
const [operation] = await client.longRunningRecognize(request);
// Get a Promise representation of the final result of the job
const [response] = await operation.promise();
const transcription = response.results
  .map(result => result.alternatives[0].transcript)
  .join('\n');
console.log(`Transcription: ${transcription}`);

PHP

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;

/** Uncomment and populate these variables in your code */
// $uri = 'The Cloud Storage object to transcribe (gs://your-bucket-name/your-object-name)';

// change these variables if necessary
$encoding = AudioEncoding::LINEAR16;
$sampleRateHertz = 32000;
$languageCode = 'en-US';

// set string as audio content
$audio = (new RecognitionAudio())
    ->setUri($uri);

// set config
$config = (new RecognitionConfig())
    ->setEncoding($encoding)
    ->setSampleRateHertz($sampleRateHertz)
    ->setLanguageCode($languageCode);

// create the speech client
$client = new SpeechClient();

// create the asyncronous recognize operation
$operation = $client->longRunningRecognize($config, $audio);
$operation->pollUntilComplete();

if ($operation->operationSucceeded()) {
    $response = $operation->getResult();

    // each result is for a consecutive portion of the audio. iterate
    // through them to get the transcripts for the entire audio file.
    foreach ($response->getResults() as $result) {
        $alternatives = $result->getAlternatives();
        $mostLikely = $alternatives[0];
        $transcript = $mostLikely->getTranscript();
        $confidence = $mostLikely->getConfidence();
        printf('Transcript: %s' . PHP_EOL, $transcript);
        printf('Confidence: %s' . PHP_EOL, $confidence);
    }
} else {
    print_r($operation->getError());
}

$client->close();

Python

from google.cloud import speech_v1
from google.cloud.speech_v1 import enums

def sample_long_running_recognize(storage_uri):
    """
    Transcribe long audio file from Cloud Storage using asynchronous speech
    recognition

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

    client = speech_v1.SpeechClient()

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

    # Sample rate in Hertz of the audio data sent
    sample_rate_hertz = 16000

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

    # Encoding of audio data sent. This sample sets this explicitly.
    # This field is optional for FLAC and WAV audio formats.
    encoding = enums.RecognitionConfig.AudioEncoding.LINEAR16
    config = {
        "sample_rate_hertz": sample_rate_hertz,
        "language_code": language_code,
        "encoding": encoding,
    }
    audio = {"uri": storage_uri}

    operation = client.long_running_recognize(config, audio)

    print(u"Waiting for operation to complete...")
    response = operation.result()

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

Ruby

# storage_path = "Path to file in Cloud Storage, eg. gs://bucket/audio.raw"

require "google/cloud/speech"

speech = Google::Cloud::Speech.speech

config = { encoding:          :LINEAR16,
           sample_rate_hertz: 16_000,
           language_code:     "en-US" }
audio = { uri: storage_path }

operation = speech.long_running_recognize config: config, audio: audio

puts "Operation started"

operation.wait_until_done!

raise operation.results.message if operation.error?

results = operation.response.results

alternatives = results.first.alternatives
alternatives.each do |alternative|
  puts "Transcription: #{alternative.transcript}"
end

로컬 파일을 사용하여 긴 오디오 파일 텍스트 변환

이 샘플은 로컬 파일을 사용하여 장기 실행 텍스트 변환 프로세스의 원시 오디오 입력을 저장합니다.

C#

static object LongRunningRecognize(string filePath)
{
    var speech = SpeechClient.Create();
    var longOperation = speech.LongRunningRecognize(new RecognitionConfig()
    {
        Encoding = RecognitionConfig.Types.AudioEncoding.Linear16,
        SampleRateHertz = 16000,
        LanguageCode = "en",
    }, RecognitionAudio.FromFile(filePath));
    longOperation = longOperation.PollUntilCompleted();
    var response = longOperation.Result;
    foreach (var result in response.Results)
    {
        foreach (var alternative in result.Alternatives)
        {
            Console.WriteLine(alternative.Transcript);
        }
    }
    return 0;
}

Go


func send(w io.Writer, client *speech.Client, filename string) error {
	ctx := context.Background()
	data, err := ioutil.ReadFile(filename)
	if err != nil {
		return err
	}

	// Send the contents of the audio file with the encoding and
	// and sample rate information to be transcripted.
	req := &speechpb.LongRunningRecognizeRequest{
		Config: &speechpb.RecognitionConfig{
			Encoding:        speechpb.RecognitionConfig_LINEAR16,
			SampleRateHertz: 16000,
			LanguageCode:    "en-US",
		},
		Audio: &speechpb.RecognitionAudio{
			AudioSource: &speechpb.RecognitionAudio_Content{Content: data},
		},
	}

	op, err := client.LongRunningRecognize(ctx, req)
	if err != nil {
		return err
	}
	resp, err := op.Wait(ctx)
	if err != nil {
		return err
	}

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

자바

/**
 * Performs non-blocking speech recognition on raw PCM audio and prints the transcription. Note
 * that transcription is limited to 60 seconds audio.
 *
 * @param fileName the path to a PCM audio file to transcribe.
 */
public static void asyncRecognizeFile(String fileName) throws Exception {
  // Instantiates a client with GOOGLE_APPLICATION_CREDENTIALS
  try (SpeechClient speech = SpeechClient.create()) {

    Path path = Paths.get(fileName);
    byte[] data = Files.readAllBytes(path);
    ByteString audioBytes = ByteString.copyFrom(data);

    // Configure request with local raw PCM audio
    RecognitionConfig config =
        RecognitionConfig.newBuilder()
            .setEncoding(AudioEncoding.LINEAR16)
            .setLanguageCode("en-US")
            .setSampleRateHertz(16000)
            .build();
    RecognitionAudio audio = RecognitionAudio.newBuilder().setContent(audioBytes).build();

    // Use non-blocking call for getting file transcription
    OperationFuture<LongRunningRecognizeResponse, LongRunningRecognizeMetadata> response =
        speech.longRunningRecognizeAsync(config, audio);

    while (!response.isDone()) {
      System.out.println("Waiting for response...");
      Thread.sleep(10000);
    }

    List<SpeechRecognitionResult> results = response.get().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

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

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

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const filename = 'Local path to audio file, e.g. /path/to/audio.raw';
// const encoding = 'Encoding of the audio file, e.g. LINEAR16';
// const sampleRateHertz = 16000;
// const languageCode = 'BCP-47 language code, e.g. en-US';

const config = {
  encoding: encoding,
  sampleRateHertz: sampleRateHertz,
  languageCode: languageCode,
};
const audio = {
  content: fs.readFileSync(filename).toString('base64'),
};

const request = {
  config: config,
  audio: audio,
};

// Detects speech in the audio file. This creates a recognition job that you
// can wait for now, or get its result later.
const [operation] = await client.longRunningRecognize(request);

// Get a Promise representation of the final result of the job
const [response] = await operation.promise();
const transcription = response.results
  .map(result => result.alternatives[0].transcript)
  .join('\n');
console.log(`Transcription: ${transcription}`);

PHP

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;

/** Uncomment and populate these variables in your code */
// $audioFile = 'path to an audio file';

// change these variables if necessary
$encoding = AudioEncoding::LINEAR16;
$sampleRateHertz = 32000;
$languageCode = 'en-US';

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

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

// set config
$config = (new RecognitionConfig())
    ->setEncoding($encoding)
    ->setSampleRateHertz($sampleRateHertz)
    ->setLanguageCode($languageCode);

// create the speech client
$client = new SpeechClient();

// create the asyncronous recognize operation
$operation = $client->longRunningRecognize($config, $audio);
$operation->pollUntilComplete();

if ($operation->operationSucceeded()) {
    $response = $operation->getResult();

    // each result is for a consecutive portion of the audio. iterate
    // through them to get the transcripts for the entire audio file.
    foreach ($response->getResults() as $result) {
        $alternatives = $result->getAlternatives();
        $mostLikely = $alternatives[0];
        $transcript = $mostLikely->getTranscript();
        $confidence = $mostLikely->getConfidence();
        printf('Transcript: %s' . PHP_EOL, $transcript);
        printf('Confidence: %s' . PHP_EOL, $confidence);
    }
} else {
    print_r($operation->getError());
}

$client->close();

Python

from google.cloud import speech_v1
from google.cloud.speech_v1 import enums
import io

def sample_long_running_recognize(local_file_path):
    """
    Transcribe a long audio file using asynchronous speech recognition

    Args:
      local_file_path Path to local audio file, e.g. /path/audio.wav
    """

    client = speech_v1.SpeechClient()

    # local_file_path = 'resources/brooklyn_bridge.raw'

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

    # Sample rate in Hertz of the audio data sent
    sample_rate_hertz = 16000

    # Encoding of audio data sent. This sample sets this explicitly.
    # This field is optional for FLAC and WAV audio formats.
    encoding = enums.RecognitionConfig.AudioEncoding.LINEAR16
    config = {
        "language_code": language_code,
        "sample_rate_hertz": sample_rate_hertz,
        "encoding": encoding,
    }
    with io.open(local_file_path, "rb") as f:
        content = f.read()
    audio = {"content": content}

    operation = client.long_running_recognize(config, audio)

    print(u"Waiting for operation to complete...")
    response = operation.result()

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

Ruby

# audio_file_path = "Path to file on which to perform speech recognition"

require "google/cloud/speech"

speech = Google::Cloud::Speech.speech

audio_file = File.binread audio_file_path
config     = { encoding:          :LINEAR16,
               sample_rate_hertz: 16_000,
               language_code:     "en-US" }
audio      = { content: audio_file }

operation = speech.long_running_recognize config: config, audio: audio

puts "Operation started"

operation.wait_until_done!

raise operation.results.message if operation.error?

results = operation.response.results

alternatives = results.first.alternatives
alternatives.each do |alternative|
  puts "Transcription: #{alternative.transcript}"
end