Riconoscere più altoparlanti in un file audio locale.
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Esempio di codice
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(
u"word: '{}', speaker_tag: {}".format(word_info.word, word_info.speaker_tag)
)
Passaggi successivi
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