转录本地多渠道文件

转录包含多个通道的本地音频文件。

深入探索

如需查看包含此代码示例的详细文档,请参阅以下内容:

代码示例

Java

如需了解如何安装和使用 Speech-to-Text 客户端库,请参阅 Speech-to-Text 客户端库。 如需了解详情,请参阅 Speech-to-Text Java API 参考文档

如需向 Speech-to-Text 进行身份验证,请设置应用默认凭证。 如需了解详情,请参阅为本地开发环境设置身份验证

/**
 * Transcribe a local audio file with multi-channel recognition
 *
 * @param fileName the path to local audio file
 */
public static void transcribeMultiChannel(String fileName) throws Exception {
  Path path = Paths.get(fileName);
  byte[] content = Files.readAllBytes(path);

  try (SpeechClient speechClient = SpeechClient.create()) {
    // Get the contents of the local audio file
    RecognitionAudio recognitionAudio =
        RecognitionAudio.newBuilder().setContent(ByteString.copyFrom(content)).build();

    // Configure request to enable multiple channels
    RecognitionConfig config =
        RecognitionConfig.newBuilder()
            .setEncoding(AudioEncoding.LINEAR16)
            .setLanguageCode("en-US")
            .setSampleRateHertz(44100)
            .setAudioChannelCount(2)
            .setEnableSeparateRecognitionPerChannel(true)
            .build();

    // Perform the transcription request
    RecognizeResponse recognizeResponse = speechClient.recognize(config, recognitionAudio);

    // Print out the results
    for (SpeechRecognitionResult result : recognizeResponse.getResultsList()) {
      // There can be several alternative transcripts for a given chunk of speech. Just use the
      // first (most likely) one here.
      SpeechRecognitionAlternative alternative = result.getAlternatives(0);
      System.out.format("Transcript : %s\n", alternative.getTranscript());
      System.out.printf("Channel Tag : %s\n", result.getChannelTag());
    }
  }
}

Node.js

如需了解如何安装和使用 Speech-to-Text 客户端库,请参阅 Speech-to-Text 客户端库。 如需了解详情,请参阅 Speech-to-Text Node.js API 参考文档

如需向 Speech-to-Text 进行身份验证,请设置应用默认凭证。 如需了解详情,请参阅为本地开发环境设置身份验证

const fs = require('fs');

// Imports the Google Cloud client library
const speech = require('@google-cloud/speech').v1;

// 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 config = {
  encoding: 'LINEAR16',
  languageCode: 'en-US',
  audioChannelCount: 2,
  enableSeparateRecognitionPerChannel: true,
};

const audio = {
  content: fs.readFileSync(fileName).toString('base64'),
};

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

const [response] = await client.recognize(request);
const transcription = response.results
  .map(
    result =>
      ` Channel Tag: ${result.channelTag} ${result.alternatives[0].transcript}`
  )
  .join('\n');
console.log(`Transcription: \n${transcription}`);

Python

如需了解如何安装和使用 Speech-to-Text 客户端库,请参阅 Speech-to-Text 客户端库。 如需了解详情,请参阅 Speech-to-Text Python API 参考文档

如需向 Speech-to-Text 进行身份验证,请设置应用默认凭证。 如需了解详情,请参阅为本地开发环境设置身份验证


from google.cloud import speech


def transcribe_file_with_multichannel(audio_file: str) -> speech.RecognizeResponse:
    """Transcribe the given audio file synchronously with multi channel.
    Args:
        audio_file (str): Path to the local audio file to be transcribed.
            Example: "resources/multi.wav"
    Returns:
         cloud_speech.RecognizeResponse: The full response object which includes the transcription results.
    """
    client = speech.SpeechClient()

    with open(audio_file, "rb") as f:
        audio_content = f.read()

    audio = speech.RecognitionAudio(content=audio_content)

    config = speech.RecognitionConfig(
        encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
        sample_rate_hertz=44100,
        language_code="en-US",
        audio_channel_count=2,
        enable_separate_recognition_per_channel=True,
    )

    response = client.recognize(config=config, audio=audio)

    for i, result in enumerate(response.results):
        alternative = result.alternatives[0]
        print("-" * 20)
        print(f"First alternative of result {i}")
        print(f"Transcript: {alternative.transcript}")
        print(f"Channel Tag: {result.channel_tag}")

    return result

Ruby

如需了解如何安装和使用 Speech-to-Text 客户端库,请参阅 Speech-to-Text 客户端库

如需向 Speech-to-Text 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证

# audio_file_path = "path/to/audio.wav"

require "google/cloud/speech"

speech = Google::Cloud::Speech.speech version: :v1

config = {
  encoding:                                :LINEAR16,
  sample_rate_hertz:                       44_100,
  language_code:                           "en-US",
  audio_channel_count:                     2,
  enable_separate_recognition_per_channel: true
}

audio_file = File.binread audio_file_path
audio      = { content: audio_file }

response = speech.recognize config: config, audio: audio

results = response.results

results.each_with_index do |result, i|
  alternative = result.alternatives.first
  puts "-" * 20
  puts "First alternative of result #{i}"
  puts "Transcript: #{alternative.transcript}"
  puts "Channel Tag: #{result.channel_tag}"
end

后续步骤

如需搜索和过滤其他 Google Cloud 产品的代码示例,请参阅Google Cloud 示例浏览器