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搭配分段標記對 Cloud Storage 中的檔案進行語音轉錄 (Beta 版)

辨識儲存在 Cloud Storage 音訊檔案中的多位說話者。

深入探索

如需包含這個程式碼範例的詳細說明文件，請參閱下列內容：

偵測錄音中不同的說話者

程式碼範例

Go

如要瞭解如何安裝及使用 Speech-to-Text 的用戶端程式庫，請參閱這篇文章。詳情請參閱 Speech-to-Text Go API 參考說明文件。

如要向語音轉文字服務進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證」。


import (
	"context"
	"fmt"
	"io"
	"strings"

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

// transcribe_diarization_gcs_beta Transcribes a remote audio file using speaker diarization.
func transcribe_diarization_gcs_beta(w io.Writer) error {
	// Google Cloud Storage URI pointing to the audio content.

	ctx := context.Background()

	client, err := speech.NewClient(ctx)
	if err != nil {
		return fmt.Errorf("NewClient: %w", err)
	}
	defer client.Close()

	diarizationConfig := &speechpb.SpeakerDiarizationConfig{
		EnableSpeakerDiarization: true,
		MinSpeakerCount:          2,
		MaxSpeakerCount:          2,
	}

	recognitionConfig := &speechpb.RecognitionConfig{
		Encoding:          speechpb.RecognitionConfig_LINEAR16,
		SampleRateHertz:   8000,
		LanguageCode:      "en-US",
		DiarizationConfig: diarizationConfig,
	}

	// Set the remote path for the audio file
	audio := &speechpb.RecognitionAudio{
		AudioSource: &speechpb.RecognitionAudio_Uri{Uri: "gs://cloud-samples-tests/speech/commercial_mono.wav"},
	}

	longRunningRecognizeRequest := &speechpb.LongRunningRecognizeRequest{
		Config: recognitionConfig,
		Audio:  audio,
	}

	operation, err := client.LongRunningRecognize(ctx, longRunningRecognizeRequest)
	if err != nil {
		return fmt.Errorf("error running recognize %w", err)
	}

	response, err := operation.Wait(ctx)
	if err != nil {
		return err
	}

	// Speaker Tags are only included in the last result object, which has only one
	// alternative.
	alternative := response.Results[len(response.Results)-1].Alternatives[0]

	wordInfo := alternative.GetWords()[0]
	currentSpeakerTag := wordInfo.GetSpeakerTag()

	var speakerWords strings.Builder

	speakerWords.WriteString(fmt.Sprintf("Speaker %d: %s", wordInfo.GetSpeakerTag(), wordInfo.GetWord()))

	// For each word, get all the words associated with one speaker, once the speaker changes,
	// add a new line with the new speaker and their spoken words.
	for i := 1; i < len(alternative.Words); i++ {
		wordInfo := alternative.Words[i]
		if currentSpeakerTag == wordInfo.GetSpeakerTag() {
			speakerWords.WriteString(" ")
			speakerWords.WriteString(wordInfo.GetWord())
		} else {
			speakerWords.WriteString(fmt.Sprintf("\nSpeaker %d: %s",
				wordInfo.GetSpeakerTag(), wordInfo.GetWord()))
			currentSpeakerTag = wordInfo.GetSpeakerTag()
		}
	}
	fmt.Fprint(w, speakerWords.String())
	return nil
}

Java

如要瞭解如何安裝及使用 Speech-to-Text 的用戶端程式庫，請參閱這篇文章。詳情請參閱 Speech-to-Text Java API 參考說明文件。

如要向語音轉文字服務進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證」。

/**
 * Transcribe a remote audio file using speaker diarization.
 *
 * @param gcsUri the path to an audio file.
 */
public static void transcribeDiarizationGcs(String gcsUri) throws Exception {
  try (SpeechClient speechClient = SpeechClient.create()) {
    SpeakerDiarizationConfig speakerDiarizationConfig =
        SpeakerDiarizationConfig.newBuilder()
            .setEnableSpeakerDiarization(true)
            .setMinSpeakerCount(2)
            .setMaxSpeakerCount(2)
            .build();

    // Configure request to enable Speaker diarization
    RecognitionConfig config =
        RecognitionConfig.newBuilder()
            .setEncoding(AudioEncoding.LINEAR16)
            .setLanguageCode("en-US")
            .setSampleRateHertz(8000)
            .setDiarizationConfig(speakerDiarizationConfig)
            .build();

    // Set the remote path for the audio file
    RecognitionAudio audio = RecognitionAudio.newBuilder().setUri(gcsUri).build();

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

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

    // Speaker Tags are only included in the last result object, which has only one alternative.
    LongRunningRecognizeResponse longRunningRecognizeResponse = response.get();
    SpeechRecognitionAlternative alternative =
        longRunningRecognizeResponse
            .getResults(longRunningRecognizeResponse.getResultsCount() - 1)
            .getAlternatives(0);

    // The alternative is made up of WordInfo objects that contain the speaker_tag.
    WordInfo wordInfo = alternative.getWords(0);
    int currentSpeakerTag = wordInfo.getSpeakerTag();

    // For each word, get all the words associated with one speaker, once the speaker changes,
    // add a new line with the new speaker and their spoken words.
    StringBuilder speakerWords =
        new StringBuilder(
            String.format("Speaker %d: %s", wordInfo.getSpeakerTag(), wordInfo.getWord()));

    for (int i = 1; i < alternative.getWordsCount(); i++) {
      wordInfo = alternative.getWords(i);
      if (currentSpeakerTag == wordInfo.getSpeakerTag()) {
        speakerWords.append(" ");
        speakerWords.append(wordInfo.getWord());
      } else {
        speakerWords.append(
            String.format("\nSpeaker %d: %s", wordInfo.getSpeakerTag(), wordInfo.getWord()));
        currentSpeakerTag = wordInfo.getSpeakerTag();
      }
    }

    System.out.println(speakerWords.toString());
  }
}

Node.js

如要瞭解如何安裝及使用 Speech-to-Text 的用戶端程式庫，請參閱這篇文章。詳情請參閱 Speech-to-Text Node.js API 參考說明文件。

如要向語音轉文字服務進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證」。

// Imports the Google Cloud client library
const speech = require('@google-cloud/speech').v1p1beta1;

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

/**
 * TODO(developer): Uncomment the following line before running the sample.
 */
// const uri = path to GCS audio file e.g. `gs:/bucket/audio.wav`;

const config = {
  encoding: 'LINEAR16',
  sampleRateHertz: 8000,
  languageCode: 'en-US',
  enableSpeakerDiarization: true,
  minSpeakerCount: 2,
  maxSpeakerCount: 2,
  model: 'phone_call',
};

const audio = {
  uri: gcsUri,
};

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

const [response] = await client.recognize(request);
const transcription = response.results
  .map(result => result.alternatives[0].transcript)
  .join('\n');
console.log(`Transcription: ${transcription}`);
console.log('Speaker Diarization:');
const result = response.results[response.results.length - 1];
const wordsInfo = result.alternatives[0].words;
// Note: The transcript within each result is separate and sequential per result.
// However, the words list within an alternative includes all the words
// from all the results thus far. Thus, to get all the words with speaker
// tags, you only have to take the words list from the last result:
wordsInfo.forEach(a =>
  console.log(` word: ${a.word}, speakerTag: ${a.speakerTag}`)
);

Python

如要瞭解如何安裝及使用 Speech-to-Text 的用戶端程式庫，請參閱這篇文章。詳情請參閱 Speech-to-Text Python API 參考說明文件。

如要向語音轉文字服務進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證」。


from google.cloud import speech


def transcribe_diarization_gcs_beta(audio_uri: str) -> bool:
    """Transcribe a remote audio file (stored in Google Cloud Storage) using speaker diarization.
    Args:
        audio_uri (str): The Google Cloud Storage path to an audio file.
            E.g., gs://[BUCKET]/[FILE]
    Returns:
        True if the operation successfully completed, False otherwise.
    """

    client = speech.SpeechClient()
    # Enhance diarization config with more speaker counts and details
    speaker_diarization_config = speech.SpeakerDiarizationConfig(
        enable_speaker_diarization=True,
        min_speaker_count=2,  # Set minimum number of speakers
        max_speaker_count=2,  # Adjust max speakers based on expected number of speakers
    )

    # Configure recognition with enhanced audio settings
    recognition_config = speech.RecognitionConfig(
        encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
        language_code="en-US",
        sample_rate_hertz=8000,
        diarization_config=speaker_diarization_config,
    )

    # Set the remote path for the audio file
    audio = speech.RecognitionAudio(
        uri=audio_uri,
    )

    # Use non-blocking call for getting file transcription
    response = client.long_running_recognize(
        config=recognition_config, audio=audio
    ).result(timeout=300)

    # The transcript within each result is separate and sequential per result.
    # However, the words list within an alternative includes all the words
    # from all the results thus far. Thus, to get all the words with speaker
    # tags, you only have to take the words list from the last result
    result = response.results[-1]
    words_info = result.alternatives[0].words

    # Print the output
    for word_info in words_info:
        print(f"word: '{word_info.word}', speaker_tag: {word_info.speaker_tag}")
    return True

後續步驟

如要搜尋及篩選其他 Google Cloud 產品的程式碼範例，請參閱Google Cloud 範例瀏覽器。

搭配分段標記對 Cloud Storage 中的檔案進行語音轉錄 (Beta 版) 透過集合功能整理內容 你可以依據偏好儲存及分類內容。

深入探索

程式碼範例

Go

Java

Node.js

Python

後續步驟

搭配分段標記對 Cloud Storage 中的檔案進行語音轉錄 (Beta 版)