Prova Gemini 1.5 Pro, il nostro modello multimodale più avanzato di Vertex AI e scopri cosa puoi creare con una finestra di contesto dei token da 1 milione. Prova Gemini 1.5 Pro, il nostro modello multimodale più avanzato di Vertex AI e scopri cosa puoi creare con una finestra di contesto di 1 milione di token.

Questa pagina è stata tradotta dall'API Cloud Translation.

Rilevare diversi interlocutori in una registrazione audio

Questa pagina descrive come ottenere etichette per diversi interlocutori nei dati audio trascritti da Speech-to-Text.

A volte i dati audio contengono campioni di più persone che parlano. Ad esempio, l'audio di una telefonata di solito include le voci di due o più persone. Una trascrizione della chiamata idealmente include chi parla e a che ora.

Speaker diarization

Speech-to-Text può riconoscere più altoparlanti nello stesso clip audio. Quando invii una richiesta di trascrizione audio a Speech-to-Text, puoi includere un parametro per indicare a Speech-to-Text di identificare i diversi altoparlanti nel campione audio. Questa funzionalità, chiamata diarizzazione degli speaker, rileva quando gli oratori cambiano e etichettano in base al numero le singole voci rilevate nell'audio.

Quando attivi la diarizzazione dello speaker nella richiesta di trascrizione, Speech-to-Text tenta di distinguere le diverse voci incluse nel campione audio. Il risultato della trascrizione tagga ogni parola con un numero assegnato ai singoli oratori. Le parole pronunciate dallo stesso oratore hanno lo stesso numero. Il risultato di una trascrizione può includere numeri fino a un numero massimo di altoparlanti che Speech-to-Text può identificare in modo univoco nel campione audio.

Quando usi la diarizzazione di chi parla, Speech-to-Text produce un aggregato in esecuzione di tutti i risultati forniti nella trascrizione. Ogni risultato include le parole del risultato precedente. Pertanto, l'array words nel risultato finale fornisce i risultati completi e diarizzati della trascrizione.

Consulta la pagina di assistenza delle lingue per sapere se questa funzionalità è disponibile nella tua lingua.

Attivare la diarizzazione dello speaker in una richiesta

Per abilitare la diarizzazione degli speaker, devi impostare il campo enableSpeakerDiarization su true nei parametri SpeakerDiarizationConfig della richiesta. Per migliorare i risultati della trascrizione, devi anche specificare il numero di interlocutori presenti nel clip audio impostando il campo diarizationSpeakerCount nei parametri SpeakerDiarizationConfig. Speech-to-Text utilizza un valore predefinito se non fornisci un valore per diarizationSpeakerCount.

Speech-to-Text supporta la diarizzazione dello speaker per tutti i metodi di riconoscimento vocale: speech:recognize speech:longrunningrecognize e Streaming.

Utilizza un file locale

Lo snippet di codice riportato di seguito mostra come abilitare la diarizzazione di una persona in una richiesta di trascrizione a Speech-to-Text

Protocollo

Per informazioni dettagliate, consulta l'endpoint API speech:recognize.

Per eseguire il riconoscimento vocale sincrono, effettua una richiesta POST e fornisci il corpo della richiesta appropriato. Di seguito è riportato un esempio di richiesta POST che utilizza curl. L'esempio utilizza Google Cloud CLI per generare un token di accesso. Per istruzioni sull'installazione di gcloud CLI, consulta la quickstart.

curl -s -H "Content-Type: application/json" \
    -H "Authorization: Bearer $(gcloud auth application-default print-access-token)" \
    https://speech.googleapis.com/v1p1beta1/speech:recognize \
    --data '{
    "config": {
        "encoding": "LINEAR16",
        "languageCode": "en-US",
        "diarizationConfig": {
          "enableSpeakerDiarization": true,
          "minSpeakerCount": 2,
          "maxSpeakerCount": 2
        },
        "model": "phone_call",
    },
    "audio": {
        "uri": "gs://cloud-samples-tests/speech/commercial_mono.wav"
    }
}' > speaker-diarization.txt

Se la richiesta ha esito positivo, il server restituisce un codice di stato HTTP 200 OK e la risposta in formato JSON, salvate in un file denominato speaker-diarization.txt.

{
  "results": [
    {
      "alternatives": [
        {
          "transcript": "hi I'd like to buy a Chromecast and I was wondering whether you could help me with that certainly which color would you like we have blue black and red uh let's go with the black one would you like the new Chromecast Ultra model or the regular Chrome Cast regular Chromecast is fine thank you okay sure we like to ship it regular or Express Express please terrific it's on the way thank you thank you very much bye",
          "confidence": 0.92142606,
          "words": [
            {
              "startTime": "0s",
              "endTime": "1.100s",
              "word": "hi",
              "speakerTag": 2
            },
            {
              "startTime": "1.100s",
              "endTime": "2s",
              "word": "I'd",
              "speakerTag": 2
            },
            {
              "startTime": "2s",
              "endTime": "2s",
              "word": "like",
              "speakerTag": 2
            },
            {
              "startTime": "2s",
              "endTime": "2.100s",
              "word": "to",
              "speakerTag": 2
            },
            ...
            {
              "startTime": "6.500s",
              "endTime": "6.900s",
              "word": "certainly",
              "speakerTag": 1
            },
            {
              "startTime": "6.900s",
              "endTime": "7.300s",
              "word": "which",
              "speakerTag": 1
            },
            {
              "startTime": "7.300s",
              "endTime": "7.500s",
              "word": "color",
              "speakerTag": 1
            },
            ...
          ]
        }
      ],
      "languageCode": "en-us"
    }
  ]
}

Go

Per scoprire come installare e utilizzare la libreria client per Speech-to-Text, consulta la pagina relativa alle librerie client di Speech-to-Text. Per maggiori informazioni, consulta la documentazione di riferimento dell'API Speech-to-Text Go.

Per eseguire l'autenticazione a Speech-to-Text, configura le Credenziali predefinite dell'applicazione. Per maggiori informazioni, consulta Configurare l'autenticazione per un ambiente di sviluppo locale.


import (
	"context"
	"fmt"
	"io"
	"os"
	"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(w io.Writer, filename string) error {
	// filename := "path-to-an-audio-file"

	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,
	}

	// Get the contents of the local audio file
	content, err := os.ReadFile(filename)
	if err != nil {
		return fmt.Errorf("error reading file %v", err)
	}
	audio := &speechpb.RecognitionAudio{
		AudioSource: &speechpb.RecognitionAudio_Content{Content: content},
	}

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

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

Java

/**
 * Transcribe the given audio file using speaker diarization.
 *
 * @param fileName the path to an audio file.
 */
public static void transcribeDiarization(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();

    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();

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

    // Speaker Tags are only included in the last result object, which has only one alternative.
    SpeechRecognitionAlternative alternative =
        recognizeResponse.getResults(recognizeResponse.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

const fs = require('fs');

// 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 lines before running the sample.
 */
// const fileName = 'Local path to audio file, e.g. /path/to/audio.raw';

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

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 => 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

from google.cloud import speech_v1p1beta1 as speech

client = speech.SpeechClient()

speech_file = "resources/commercial_mono.wav"

with open(speech_file, "rb") as audio_file:
    content = audio_file.read()

audio = speech.RecognitionAudio(content=content)

diarization_config = speech.SpeakerDiarizationConfig(
    enable_speaker_diarization=True,
    min_speaker_count=2,
    max_speaker_count=10,
)

config = speech.RecognitionConfig(
    encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
    sample_rate_hertz=8000,
    language_code="en-US",
    diarization_config=diarization_config,
)

print("Waiting for operation to complete...")
response = client.recognize(config=config, audio=audio)

# 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

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

return result

utilizza un bucket Cloud Storage

Il seguente snippet di codice mostra come attivare la diarizzazione di una persona in una richiesta di trascrizione a Speech-to-Text

Go


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, gcsUri string) error {
	// Google Cloud Storage URI pointing to the audio content.
	// gcsUri := "gs://bucket-name/path_to_audio_file"

	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: gcsUri},
	}

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

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

Java

/**
 * 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

// 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


from google.cloud import speech

def transcribe_diarization_gcs_beta(gcs_uri: str) -> bool:
    """Transcribe a remote audio file (stored in Google Cloud Storage) using speaker diarization.

    Args:
        gcs_uri: The Google Cloud Storage path to an audio file.

    Returns:
        True if the operation successfully completed, False otherwise.
    """

    client = speech.SpeechClient()

    speaker_diarization_config = speech.SpeakerDiarizationConfig(
        enable_speaker_diarization=True,
        min_speaker_count=2,
        max_speaker_count=2,
    )

    # Configure request to enable Speaker diarization
    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=gcs_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