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The Translation model generates translations of your transcriptions to one or more targeted languages. If subtitles and/or sentences are enabled, the translations will also include translated results for them. You can translate your transcription to multiples languages in a single API call.

The list of the languages covered by the Translation feature are listed in the API Reference (see translation_config).

2 translation models are available:

  • base : Fast, cover most use cases
  • enhanced : Slower, but higher quality and with context awareness

In the following examples, we’re using base model.

async function makeFetchRequest(url: string, options: any) {
  const response = await fetch(url, options);
  return response.json();
}

async function pollForResult(resultUrl: string, headers: any) {
  while (true) {
    console.log("Polling for results...");
    const pollResponse = await makeFetchRequest(resultUrl, { headers });

    if (pollResponse.status === "done") {
      console.log("- Transcription done: \n");
      const translation = pollResponse.result.translation;
      console.log(translation);
      break;
    } else {
      console.log("Transcription status : ", pollResponse.status);
      await new Promise((resolve) => setTimeout(resolve, 1000));
    }
  }
}

async function startTranscription() {
  const gladiaKey = "YOUR_GLADIA_API_TOKEN";
  const requestData = {
    audio_url:
      "YOUR_AUDIO_URL",
    translation: true,
    translation_config: {
      target_languages: [ "fr", "es"],
      model: "base" // "enhanced" is slower but of better quality
    }
  };
  const gladiaUrl = "https://api.gladia.io/v2/transcription/";
  const headers = {
    "x-gladia-key": gladiaKey,
    "Content-Type": "application/json",
  };

  console.log("- Sending initial request to Gladia API...");
  const initialResponse = await makeFetchRequest(gladiaUrl, {
    method: "POST",
    headers,
    body: JSON.stringify(requestData),
  });

  console.log("Initial response with Transcription ID :", initialResponse);

  if (initialResponse.result_url) {
    await pollForResult(initialResponse.result_url, headers);
  }
}

startTranscription();

With this code, your output will look like this:

{
  success: true,
  is_empty: false,
  results: [
    {
      words: [
        {
          word: "Diviser",
          start: 0.20043,
          end: 0.7008000000000001,
          confidence: 1
        },
        {
          word: "l'infini",
          start: 0.9009500000000001,
          end: 1.5614400000000002,
          confidence: 1
        },
        ...
      ],
      languages: [Array],
      full_transcript: "Diviser l'infini dans un temps où moins est plus...",
      utterances: [Array], // Also translated
      error: null
    },
    {
      words: [
        {
          word: "Dividir",
          start: 0.20043,
          end: 0.7008000000000001,
          confidence: 1
        },
        {
          word: "la infinidad",
          start: 0.9009500000000001,
          end: 1.5614400000000002,
          confidence: 1
        },
        ...
      ],
      languages: [Array],
      full_transcript: "Dividir la infinidad en un tiempo en que menos es más, donde demasiado nunca es suficiente...",
      utterances: [Array], // Also translated
      error: null
    }
  ],
  exec_time: 0.6475496292114258,
  error: null
}

If you enabled the subtitles generation, those will also benefits from the translation model.

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