转录长音频文件

本页面演示了如何使用异步语音识别将长音频文件(时长超过 1 分钟)转录为文字。

异步语音识别功能会启动一项长时间运行的音频处理操作。使用异步语音识别可以识别时长超过一分钟的音频。对于较短的音频,同步语音识别更为简单快捷。

您可以通过 google.longrunning.Operations 接口检索操作结果。搜索结果在 5 天(120 小时)内可供检索。Speech-to-Text 可以直接接收音频内容,也可以处理已存在于 Google Cloud Storage 中的音频内容。另请参阅异步语音识别请求的音频限制

使用 Google Cloud Storage 文件转录长音频文件

这些示例使用 Cloud Storage 存储分区来存储长音频转录过程的原始音频输入。

协议

如需了解完整的详细信息,请参阅 speech:longrunningrecognize API 端点。

如需执行同步语音识别,请发出 POST 请求并提供相应的请求正文。以下示例展示了一个使用 curl 发出的 POST 请求。该示例使用通过 Google Cloud Cloud SDK 为项目设置的服务帐号的访问令牌。如需了解有关安装 Cloud SDK、建立项目和服务帐号以及获取访问令牌的说明,请参阅快速入门

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"

如需详细了解配置请求正文的信息,请参阅 RecognitionConfigRecognitionAudio 参考文档。

如果请求成功,服务器将返回一个 200 OK HTTP 状态代码以及 JSON 格式的响应:

{
  "name": "7612202767953098924"
}

其中,name 是为请求创建的长时间运行的操作的名称。

等待处理完成。处理时间因来源音频而异。在大多数情况下,您只需等待源音频长度的一半时间即可获得结果。向 https://speech.googleapis.com/v1/operations/ 端点发出 GET 请求即可获取长时间运行的操作的状态。请将 your-operation-name 替换为 longrunningrecognize 请求返回的 name。您可以从 progressPercent 字段获取请求的预估进度。

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"

如果请求成功,服务器将返回一个 200 OK HTTP 状态代码以及 JSON 格式的响应:

{
  "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": [
          {
            ...
          }
        ]
      }
    ]
  }
}

如果该操作尚未完成,则可以通过反复发出 GET 请求来轮询此端点,直到相应响应的 done 属性为 true 为止。

gcloud 命令

如需查看完整的详细信息,请参阅 recognize-long-running 命令。

要执行异步语音识别,请使用 gcloud 命令行工具,并提供本地文件的路径或 Google Cloud Storage 网址。

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

如果请求成功,则服务器以 JSON 格式返回长时间运行的操作的 ID。

{
  "name": OPERATION_ID
}

然后,您可以通过运行以下命令来获取该操作的信息。

gcloud ml speech operations describe OPERATION_ID

您也可以通过运行以下命令来轮询该操作,直到它完成为止。

gcloud ml speech operations wait OPERATION_ID

该操作完成后,它会以 JSON 格式返回音频。

{
  "@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
}

Java

/**
 * 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

使用本地文件转录长音频文件

这些示例使用本地文件来存储长音频转录过程的原始音频输入。

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
}

Java

/**
 * 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